Journal articles: 'Autocorrelation function (ACF)'

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LEE, CHOONG-HOON, HEUNG-KYU LEE, and YOUNGHO SUH. "IMAGE WATERMARKING RESISTANT TO COMBINED GEOMETRIC AND REMOVAL ATTACKS." International Journal of Image and Graphics 05, no. 01 (January 2005): 37–65. http://dx.doi.org/10.1142/s0219467805001653.

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In this paper, we propose an improved autocorrelation function (ACF)-based watermarking that is robust against combined geometric and removal attacks. ACF-based watermarking is known to be effective against geometric attacks. In this watermarking scheme, both the embedded watermark and autocorrelation peaks of the watermark should survive a variety of attacks. However, the autocorrelation peaks are not strong enough. The proposed method improves the robustness of ACF-based watermarking by enhancing the strength of the autocorrelation peaks. Instead of the simple addition of a watermark to an image, the proposed watermark embedder uses the information of an original image more actively during the embedding process, so that the marked image has strong autocorrelation peaks. Experimental results show that the proposed scheme provides better robustness than conventional ACF-based watermarking against a variety of combined geometric-removal attacks.

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Bykhovsky, Dima, and Tom Trigano. "Numerical Generation of Compound Random Processes with an Arbitrary Autocorrelation Function." Fluctuation and Noise Letters 17, no. 01 (January 23, 2018): 1850001. http://dx.doi.org/10.1142/s0219477518500013.

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The generation of non-Gaussian random processes with a given autocorrelation function (ACF) is addressed. The generation is based on a compound process with two components. Both components are solutions of appropriate stochastic differential equations (SDEs). One of the components is a Gaussian process and the other one is non-Gaussian with an exponential ACF. The analytical study shows that a compound combination of these processes may be used for the generation of a non-Gaussian random process with a required ACF. The results are verified by two numerical examples.

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Li, Ming, and Wei Zhao. "Convergence of Sample Autocorrelation of Long-Range Dependent Traffic." Mathematical Problems in Engineering 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/725730.

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We depict our work on a fundamental issue in the theory of long-range dependent traffic in the aspect of the convergence of sample autocorrelation function (ACF) of real traffic. The present results suggest that the sample ACF of traffic is convergent. In addition, we show that the sample size has considerable effects in estimating the sample ACF of traffic. More precisely, a sample ACF of traffic tends to be smoother when the sample size increases.

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Korobeinikov, A. V. "Fast algorithm for calculating autocorrelation function in code synthesis tasks by enumerative technique." Issues of radio electronics 1, no. 1 (March 13, 2021): 13–18. http://dx.doi.org/10.21778/2218-5453-2021-1-13-18.

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The fast algorithm for calculating the autocorrelation function (ACF) of a binary code is developed in relation to the problem of synthesizing codes with a given ACF by enumerative technique. The algorithm is applicable for any duration of the N code. The computational complexity of calculating the ACF is 2N multiplication operations and 2N addition operations. The linear dependence of computational complexity on the duration of the N code is noted. To calculate the ACF of the newly created code combination, the previous code, its ACF, and the index of the changed code element are used. The condition of applicability of the algorithm is that the search of code combinations must be performed by changing only one element in the current code combination. An enumerative technique is proposed that allows a complete enumertion of all 2N existing combinations by sequentially changing the code combination of just one element.

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Li, Ming, and Wei Zhao. "Smoothing the Sample Autocorrelation of Long-Range-Dependent Traffic." Mathematical Problems in Engineering 2013 (2013): 1–10. http://dx.doi.org/10.1155/2013/631498.

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This paper depicts our work in smoothing the sample autocorrelation function (ACF) of traffic. The experimental results exhibit that the sample ACF of traffic may be smoothed by the way of average. In addition, the results imply that the sum of sample ACFs of traffic convergences. Considering that the traffic data used in this research is long-range dependent (LRD), the latter may be meaningful for the theoretical research of LRD traffic.

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EL-KHAMY, S. E., M. M. HADHOUD, M. I. DESSOUKY, B. M. SALAM, and F. E. ABD EL-SAMIE. "ACQUISITION OF SARSAT INFORMATION USING AN AUTO-CORRELATION BASED ADAPTIVE LINE ENHANCER." International Journal of Information Acquisition 02, no. 04 (December 2005): 291–302. http://dx.doi.org/10.1142/s0219878905000659.

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This paper develops a new approach to the detection of the emergency locator transmitter (ELT) signal using an adaptive line enhancer (ALE). The input signal to the ALE is replaced by its autocorrelation function (ACF) because noise affects the central samples of the autocorrelation function only while it affects all samples of the noisy signal. This gives the ALE the ability to get rid of noise, easily. The output ACF is then used in the spectral estimation and detection of the ELT signal. This approach is related to the signal processing using Higher Order Statistics (HOS) since the ACF is the used input. The paper also compares the results of the new approach to other different previously used methods foe ELT signal detection. The first method uses the signal xk as an input to the ALE, and the second method uses [Formula: see text]. Results illustrate the superiority of the proposed method over the other two methods. A comparison study between the performance of two types of ALE; Fixed pole radius and variable pole radius ALEs in detecting the ELT signal, is introduced.

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ANISHCHENKO, VADIM S., TATJANA E. VADIVASOVA, ANDREY S. KOPEIKIN, GALINA I. STRELKOVA, and JÜRGEN KURTHS. "SPECTRAL AND CORRELATION ANALYSIS OF SPIRAL CHAOS." Fluctuation and Noise Letters 03, no. 02 (June 2003): L213—L221. http://dx.doi.org/10.1142/s0219477503001282.

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We study numerically the behavior of the autocorrelation function (ACF) and the power spectrum of spiral attractors without and in the presence of noise. It is shown that the ACF decays exponentially and has two different time scales. The rate of the ACF decrease is defined by the amplitude fluctuations on small time intervals, i.e., when τ < τ cor , and by the effective diffusion coefficient of the instantantaneous phase on large time intervals. It is also demonstrated that the ACF in the Poincare map also decreases according to the exponential law exp (- λ+ k), where λ+ is the positive Lyapunov exponent. The obtained results are compared with the theory of fluctuations for the Van der Pol oscillator.

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Li, Ming. "Power Spectrum of Generalized Fractional Gaussian Noise." Advances in Mathematical Physics 2013 (2013): 1–3. http://dx.doi.org/10.1155/2013/315979.

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Recently, we introduced a type of autocorrelation function (ACF) to describe a long-range dependent (LRD) process indexed with two parameters, which takes standard fractional Gaussian noise (fGn for short) as a special case. For simplicity, we call it the generalized fGn (GfGn). This short paper gives the power spectrum density function (PSD) of GfGn.

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Shitan, Mahendran, and Shelton Peiris. "A Note on the Properties of Generalised Separable Spatial Autoregressive Process." Journal of Probability and Statistics 2009 (2009): 1–11. http://dx.doi.org/10.1155/2009/847830.

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Spatial modelling has its applications in many fields like geology, agriculture, meteorology, geography, and so forth. In time series a class of models known as Generalised Autoregressive (GAR) has been introduced by Peiris (2003) that includes an index parameterδ. It has been shown that the inclusion of this additional parameter aids in modelling and forecasting many real data sets. This paper studies the properties of a new class of spatial autoregressive process of order 1 with an index. We will call this aGeneralised Separable Spatial Autoregressive(GENSSAR) Model. The spectral density function (SDF), the autocovariance function (ACVF), and the autocorrelation function (ACF) are derived. The theoretical ACF and SDF plots are presented as three-dimensional figures.

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Chui, Ming Wei, You Qian Feng, Wei Wang, Pei Lin Li, and Zheng Chao Li. "Numerical Simulation of Rough Surface with Crossed Texture." Applied Mechanics and Materials 321-324 (June 2013): 196–200. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.196.

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To meet the demands for rough surfaces data in the research of surface engineering, contacts characteristic and so on, a new numerical simulation of rough surface is proposed. Based on FFT method, rough surface with single direction texture is simulated with circular cosine-exponent autocorrelation function (ACF), and the generated surface is rotated of different given angles respectively by rotation of reference system, then the rough surface with multi-direction texture is created by synthesizing the rotated surfaces. The simulation results show that, the ACF curves of generated surface is periodic fluctuation decay, and has a good fitting result with the predetermined ACF. The contrast result between simulated surface and measured surface shows the available of the proposed method.

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Zhang, Yan Min, Xing Guang Qi, and Qing Hua Li. "Simulation of Dynamic Light Scattering Signal Based on AR Model." Applied Mechanics and Materials 571-572 (June 2014): 840–44. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.840.

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According to the autocorrelation function (ACF) of the ultrafine particles, the auto-regressive (AR) model used for dynamic light scattering (DLS) signals simulation can be established. By the method, DLS signals for nanoparticles distribution are simulated respectively and every ACF of simulation signal performs a great agreement with its theory value. The simulation signals were respectively inversed and inversion errors are less than 5.25%. The particles size inversions of Photon Correlation Spectroscopy (PCS) are obtained by Morozov discrepancy principle. Experiments show that the method based on AR model is feasible in DLS signal simulation.

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Sumioka, T., and Y. Ando. "On the pitch identification of complex tones by the autocorrelation function (ACF) model." Journal of the Acoustical Society of America 100, no. 4 (October 1996): 2720. http://dx.doi.org/10.1121/1.416159.

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Zhong, Xin, Chi Hang Zhao, and Jie He. "Study on Four Parameters Estimation’s Methods of Time-Series Model in Modeling the Signal of a Quartz Flex Accelerometer." Applied Mechanics and Materials 128-129 (October 2011): 329–32. http://dx.doi.org/10.4028/www.scientific.net/amm.128-129.329.

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Box-Jenkins method of time series in modeling the signal of quartz flex accelerometer is studied in the paper. Firstly, a JSD-I/A quartz flex accelerometer is placed on a level test bench, and the output signal of the JSD-I/A quartz flex accelerometer is acquired. Secondly, the acquired signal of the JSD-I/A quartz flex accelerometer is preprocessed by Db3 wavelet denoising, trend items exacting, and standardized processing. Thirdly, The statistical characteristics of autocorrelation function (ACF) and partial autocorrelation function (PACF) of the processed time series data are analyzed, and the results show that ACF presents tailing characteristic and PACF presents censoring characteristic after 12th order. So AR(12) model is suitable for modeling the processed data of the JSD-I/A quartz flex accelerometer. Fourthly, the AR(12) model’s parameters are estimated by four methods, named least square method (LSM), Yule-Walker method, LUD method and Burg method, respectively. The fitting effects by residuals sum of squares (RSS) of the above estimation methods are compared and the results show that LSM outperforms the other three estimation methods.

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Li, Ming, and Wei Zhao. "Variance Bound of ACF Estimation of One Block of fGn with LRD." Mathematical Problems in Engineering 2010 (2010): 1–14. http://dx.doi.org/10.1155/2010/560429.

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This paper discusses the estimation of autocorrelation function (ACF) of fractional Gaussian noise (fGn) with long-range dependence (LRD). A variance bound of ACF estimation of one block of fGn with LRD for a given value of the Hurst parameter (H) is given. The present bound provides a guideline to require the block size to guarantee that the variance of ACF estimation of one block of fGn with LRD for a givenHvalue does not exceed the predetermined variance bound regardless of the start point of the block. In addition, the present result implies that the error of ACF estimation of a block of fGn with LRD depends only on the number of data points within the sample and not on the actual sample length in time. For a given block size, the error is found to be larger for fGn with stronger LRD than that with weaker LRD.

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CHOI, HYUNG WOOC, SEONG EUN MAENG, and JAE WOO LEE. "EFFECTS OF INTRADAY PATTERNS ON ANALYSIS OF STOCK MARKET INDEX AND TRADING VOLUME." International Journal of Modern Physics: Conference Series 16 (January 2012): 41–50. http://dx.doi.org/10.1142/s2010194512007763.

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We review the stylized properties of the stock market and consider effects of the intraday patterns on the analysis of the time series for the stock index and the trading volume in Korean stock market. In the stock market the probability distribution function (pdf) of the return and volatility followed the power law for the stock index and the change of the volume traded. The volatility of the stock index showed the long-time memory and the autocorrelation function followed a power law. We applied two eliminating methods of the intraday patterns: the intraday patterns of the time series itself, and the intraday patterns of the absolute return for the index or the absolute volume change. We scaled the index and return by two types of the intraday patterns. We considered the probability distribution function and the autocorrelation function (ACF) for the time series scaled by the intraday patterns. The cumulative probability distribution function of the returns scaled by the intraday patterns showed a power law, P>(r) ~ r-α±, where α± corresponds to the exponent of the positive and negative fat tails. The pdf of the return scaled by intraday patterns by the absolute return decayed much steeper than that of the return scaled by intraday patterns of the index itself. The pdf for the volume change also followed the power law for both methods of eliminating intraday patterns. However, the exponents of the power law at fat tails do not depend on the intraday patterns. The ACF of the absolute return showed long-time correlation and followed the power law for the scaled index and for the scaled volume. The daily periodicity of the ACF was removed for scaled time series by the intraday patterns of the absolute return or the absolute volume change.

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Zuo, Jiajun, Ruijuan Yang, Shaohua Luo, and Xiaobai Li. "Training Sequence Design of TDS-OFDM Signal in Joint Radar and Communication System." Mathematical Problems in Engineering 2019 (July 30, 2019): 1–10. http://dx.doi.org/10.1155/2019/3914314.

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In the joint radar and communication system, using orthogonal frequency division multiplexing (OFDM) signals, cyclic prefix (CP) and pilots lead to the problem of high peak at the sidelobe (PSL) level in autocorrelation function (ACF), which deteriorates the radar detection performance seriously. To solve this problem, first, a new RadCom signal based on time-domain synchronization OFDM (TDS-OFDM) was proposed. TDS-OFDM adopts training sequence (TS) for guard interval, as well as synchronization and channel estimation, so that CP and pilots can be avoided. And then, ambiguity function (AF) of TDS-OFDM RadCom signal was analyzed. Finally, TS are optimized to suppress PSL of TDS-OFDM signal and maintain the autocorrelation properties of TS simultaneously. The results show that the autocorrelation performance of designed TDS-OFDM RadCom signal is much better than that of CP-OFDM RadCom signal. Considering the importance of radar target detection, TDS-OFDM is more appropriate than CP-OFDM for the RadCom system.

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Papamarkou, T., and A. J. Lawrance. "Nonlinear Dynamics of Trajectories Generated by Fully-Stretching Piecewise Linear Maps." International Journal of Bifurcation and Chaos 24, no. 05 (May 2014): 1450071. http://dx.doi.org/10.1142/s0218127414500710.

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This paper focuses on the nonlinear dynamical properties of chaotic orbits iteratively generated by maps composed of linear branches which expand across the whole map range. The nonlinear dynamics of such orbits involve both their statistical and chaotic properties. More specifically, analytical expressions are provided for the mean-adjusted quadratic autocorrelation function (ACF) and for the Lyapunov exponent of trajectories produced by the considered collection of piecewise linear maps.

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Chen, L. J., S. L. Cheng, C. H. Yu, P. Y. Su, H. H. Lin, and K. S. Chi. "Structural Evolution in Amorphous Silicon and Germanium Thin Films." Microscopy and Microanalysis 8, no. 4 (August 2002): 268–73. http://dx.doi.org/10.1017/s1431927602020202.

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The structural evolution in amorphous silicon and germanium thin films has been investigated by high-resolution transmission electron microscopy (HRTEM) in conjunction with autocorrelation function (ACF) analysis. The results established that the structure of as-deposited semiconductor films is of a high density of nanocrystallites embedded in the amorphous matrix. In addition, from ACF analysis, the structure of a-Ge is more ordered than that of a-Si. The density of embedded nanocrystallites in amorphous films was found to diminish with annealing temperature first, then to increase. The conclusions also corroborate well with the results of diminished medium-range order in annealed amorphous films determined previously by a variable coherence microscopy method.

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Zhang, Feng Wang, Wen Gang Che, Bei Bei Xu, and Jing Zhi Xu. "The Research of ARMA Model in CPI Time Series." Applied Mechanics and Materials 347-350 (August 2013): 3099–103. http://dx.doi.org/10.4028/www.scientific.net/amm.347-350.3099.

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The changing trend of CPI to a certain extent reflects the degree of inflation, which has a great significance on macro-control and research on national economic. ARMA model is one of the simple and practical models in financial time series analysis with relatively high forecast accuracy. The paper utilizing Eviews software, through the statistical analysis of CPI from the year of 1995 to 2008 monthly in China, through the ADF unit root test [, by dint of the autocorrelation function ACF diagram [ and partial autocorrelation function PACF diagram [ to identify the model consequently establish the model, through the residual serial correlation test of the residuals of the model to select the correct model [. The predications of the model showed that the ARMA model is valid and forecast accuracy is relatively high

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Tatekura, Yosuke, Yusuke Honda, and Takayoshi Nakai. "Suitable Truncation of Room Impulse Response for Inverse Filter Design of Sound Reproduction System." Advanced Materials Research 222 (April 2011): 372–75. http://dx.doi.org/10.4028/www.scientific.net/amr.222.372.

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This paper introduces an automatic decision method for designing parameters of inverse filters to simplify realization of a high-performance sound reproduction system. The reproduced performance depends on several design parameters of the inverse filters that cancel the effect of room transfer functions (RTFs). Therefore, a method of determining the sample lengths of impulse responses of RTFs is proposed. In the proposed method, a suitable sample length of the impulse response is determined based on autocorrelation function (ACF) . The results of numerical simulations using real data reveal that the proposed method can determine suitable sample lengths while maintaining reproduction performance.

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Li, Yue, Di Zhang, Ilker Capoglu, Karl A. Hujsak, Dhwanil Damania, Lusik Cherkezyan, Eric Roth, et al. "Measuring the Autocorrelation Function of Nanoscale Three-Dimensional Density Distribution in Individual Cells Using Scanning Transmission Electron Microscopy, Atomic Force Microscopy, and a New Deconvolution Algorithm." Microscopy and Microanalysis 23, no. 3 (April 18, 2017): 661–67. http://dx.doi.org/10.1017/s1431927617000447.

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AbstractEssentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass–density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass–density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass–density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass–density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass–density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes.

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Korobeynikov, A. V. "Synthesis of a packet of pulse with phase manipulation with side lobes level 1/N at incoherent accumulation." Issues of radio electronics 49, no. 5 (July 5, 2020): 28–34. http://dx.doi.org/10.21778/2218-5453-2020-5-28-34.

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The paper is devoted to the problem of choosing a probing radar signal using optimal processing of a packet of pulses with unknown initial phases. A method for synthesizing a packet of phase-coded pulses is proposed, the total autocorrelation function (ACF) of which, with coordinated filtering and incoherent accumulation, has a side lobes level (SLL) of 1/N. The search criteria for binary codes for phase manipulation of a signal that are potentially capable of forming packets of pulses with relative SLL of 1/N are formulated and justified. An algorithm has been developed for searching codes with a given ACF using the exhaustive search method. A method is proposed for forming the composition of a packets of pulses based on the exhaustive search method. A number of values of the code N duration were determined for which there are packets of pulses with a relative SLL of the total ACF equal to 1/N with coordinated filtering and incoherent accumulation.

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Rosli, Siti Julia, Hasliza Rahim, Ruzelita Ngadiran, K. N. Abdul Rani, Muhammad Imran Ahmad, and Wee Fwen Hoon. "Design of Binary Coded Pulse Trains with Good Autocorrelation Properties for Radar Communications." MATEC Web of Conferences 150 (2018): 06016. http://dx.doi.org/10.1051/matecconf/201815006016.

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Finite length of sequences that are modulated both in phase and amplitude and have an ideal autocorrelation function (ACF) consisting of merely a pulse have many applications in control and communication systems. They are widely applied in control and communication systems, such as in pulse compression systems for radar and deep-space ranging problems [1-5]. In radar design, the important part is to choose a waveform, which is suitable to be transmitted because the waveform controls resolution in clutter performance. In addition, it can solve a general signal problem particularly related to the digital processing. Energy ratio (ER), total side lobe energy (SLE), and peak sidelobe level (PSL) are three properties of such sequences interest. This paper presents a method using the Complementation, Cyclic Shift and Bit Addition for synthesizing and optimizing a binary sequence implemented to improve the sequences of a similar quality with the Barker sequence, particularly for lengths greater than 13. All of these methods are guided by the specific parameter with good characteristics in ACF (ER, SLE, and PSL) [6,7,8]. Such sequences can then be effectively used to improve the range and Doppler resolution of radars.

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VASQUEZ, NICOLAS, and NOBUYUKI KAWAI. "PULSE CHARACTERIZATION OF GRBs WITH KNOWN REDSHIFT." International Journal of Modern Physics D 19, no. 06 (June 2010): 997–1002. http://dx.doi.org/10.1142/s0218271810016798.

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Gamma-ray Bursts (GRBs) are one of the most promising tools in the study of cosmology. The luminosity, energy, light curve parameters and spectral measures could yield to the calibration of standard candles in the Universe. Nevertheless, cosmological and non-cosmological effects are not well understood. Aiming to clarify the possible effects, we started to study the autocorrelation function (ACF) of a sample of GRBs with known redshift in the combined band of Swift (15–150 keV) and Suzaku (50 keV–5 Mev) satellites. We first confirmed the bimodal distribution of the cosmological corrected ACF reported by Borgonovo et al., then looking at the energy evolution we found a bimodal distribution of the decay index of the ACF. For the next step we explored the intrinsic effects of the pulses within GRBs, determining the ACF of individual pulses at two different energy bands, as well as the skewness of the pulse. We found two kinds of internal effects, the increase of the asymmetry of the pulse with energy and the variability-dependence on energy. Two types of pulses are distinguished, suggesting more than one physical process during the prompt emission.

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Thaib, Ilham, Gesit Thabrani, and Silvia Netsyah. "Peramalan dan deteksi outlier saham perusahaan angkutan laut umum di masa covid-19 dengan pemodelan arima." Jurnal Kajian Manajemen dan Wirausaha 3, no. 1 (June 30, 2021): 8. http://dx.doi.org/10.24036/jkmw02114850.

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The public sea freight sector is one of the affected by COVID-19. PT. Samudera Indonesia Tbk is one of the sea transportations companies in Indonesia. The ARIMA model in the previous study provided a statistical test with the aim of evaluating the suitability of the model with a p value of less than 0.05 to determine ARIMA by guessing through ACF (Autocorrelation Function) and PACF (Partial Autocorrelation Function) through stationary data. Outlier detection can be done by plotting the residuals from the specified model. Forecasting data for the next 5 days using the ARIMA (3,1,2) model can be seen that the results of forecasting stock price data for PT. Samudera Indonesia Tbk using ARIMA (3,1,2) is within the 95% confidence interval with a forecast value that is close to the actual value. There are outliers that are detected which are related to economic phenomena.Keywords: Forecasting, Covid-19, stock, ARIMA, outlier

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Ksendzuk, A. V., and K. O. Kozlov. "ADAPTIVE CORRELATOR IN NON-EMITTING RADAR SYSTEMS." Issues of radio electronics, no. 3 (March 20, 2019): 41–45. http://dx.doi.org/10.21778/2218-5453-2019-3-41-45.

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The paper discusses a new method of processing information in non‑emitting radar systems, whose work is based on the use of a signal from third‑party sources – television and radio broadcasting transmitters, as well as cellular base stations. An adaptive correlator for such radar stations is proposed. The method is based on the analysis of the autocorrelation function (ACF) of a transmitter signal and the adaptive formation of detection areas, based on the properties of the current ACF. Statistical quality parameters were introduced to evaluate the developed method and these parameters were estimated for the DVB‑T2 (Digital Video Broadcasting – Terrestrial) signal, in particular, the achievable characteristics by the side lobes of the lag time uncertainty function for such a signal are shown. It is noted that several adaptive correlators should be simultaneously implemented in non‑radiant radar. The results of processing real data confirm the effectiveness of the proposed method.

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Li, Jiangnan, Zhian Sun, and Feng Zhang. "Accounting for the surface temperature persistence by using signal energy." Theoretical and Applied Climatology 144, no. 1-2 (February 9, 2021): 363–77. http://dx.doi.org/10.1007/s00704-020-03493-w.

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AbstractThe autocorrelation function (ACF) and its finite Fourier transform, referred to as signal energy, have been investigated using the ECMWF daily surface temperature data. ACF itself provides a measure of the influence of leading fluctuation between two different time points. Considering the decay of ACF, it is found that the scaling power-rule of ACF is only valid in a very short period, as the decay of ACF exists before it reaches a random noise state. Therefore, the method of the critical exponent of ACF is limited in the short length of the temporal interval. On the other hand, the distributions of the signal energy always show nice patterns, indicating the degree of persistence change. It is found, for a short period, that the distributions of the signal energy and the critical exponent are very similar, with a correlation coefficient over 0.97. For a longer period, though the critical exponent of ACF becomes invalid, the signal energy can always provide an effective method to investigate climate persistence in different lengths of time. In a 5-day period of boreal winter, the southern part of North America has a larger value of signal energy compared to the northern part; thus, the surface temperature is more stable in the north part. The result becomes opposite in the boreal summer. The method of signal energy can also be applied to a particular interval of time. In different temporal intervals, the signal energy presents very different results, especially over the El Nino regions

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Wu, Hua Bing, Jun Liang Liu, Yuan Zhang, and Yong Hui Hu. "An Improved Acquisition Method for High-Order BOC-Modulated Signals Based on Fractal Geometry." Advanced Materials Research 846-847 (November 2013): 1185–88. http://dx.doi.org/10.4028/www.scientific.net/amr.846-847.1185.

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This paper proposes an improved acquisition method for high-order binary-offset-carrier (BOC) modulated signals based on fractal geometry. We introduced the principle of our acquisition method, and outlined its framework. We increase the main peak to side peaks ratio in the BOC autocorrelation function (ACF), with a simple fractal geometry transform. The proposed scheme is applicable to both generic high-order sine-and cosine-phased BOC-modulated signals. Simulation results show that the proposed method increases output signal to noise ratio (SNR).

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André, R., M. Pinnock, J. P. Villain, and C. Hanuise. "Influence of magnetospheric processes on winter HF radar spectra characteristics." Annales Geophysicae 20, no. 11 (November 30, 2002): 1783–93. http://dx.doi.org/10.5194/angeo-20-1783-2002.

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Abstract. This study investigates further the relationship between regions of the magnetosphere and the characteristics of HF radar Doppler spectra recorded in the ionospheric projection of those regions. It builds on earlier work, which has reported a relationship between the Doppler spectral width and the ionospheric projection of the magnetospheric cusp region, by introducing novel techniques for classifying the Doppler spectra recorded by the SuperDARN radars. We first review the geophysical factors that can condition the characteristics of the autocorrelation function (ACF) data produced by the radars. This leads to a classification scheme of the ACF data which is then applied to a large database compiled from winter data taken by the Northern Hemisphere Super-DARN radars. This statistical study shows that the ACF characteristics are not randomly distributed in space, but rather are spatially organized in the ionosphere. This paper suggests that these regions are ordered primarily by the low energy (<approx> 1 keV) electron precipitation region and the presence of intense ULF wave activity.Key words. Ionosphere (auroral ionosphere; ionosphere-magnetosphere interactions; plasma convection)

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Martínez-Acosta, Luisa, Juan Pablo Medrano-Barboza, Álvaro López-Ramos, John Freddy Remolina López, and Álvaro Alberto López-Lambraño. "SARIMA Approach to Generating Synthetic Monthly Rainfall in the Sinú River Watershed in Colombia." Atmosphere 11, no. 6 (June 8, 2020): 602. http://dx.doi.org/10.3390/atmos11060602.

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Seasonal Auto Regressive Integrative Moving Average models (SARIMA) were developed for monthly rainfall time series. Normality of the rainfall time series was achieved by using the Box Cox transformation. The best SARIMA models were selected based on their autocorrelation function (ACF), partial autocorrelation function (PACF), and the minimum values of the Akaike Information Criterion (AIC). The result of the Ljung–Box statistical test shows the randomness and homogeneity of each model residuals. The performance and validation of the SARIMA models were evaluated based on various statistical measures, among these, the Student’s t-test. It is possible to obtain synthetic records that preserve the statistical characteristics of the historical record through the SARIMA models. Finally, the results obtained can be applied to various hydrological and water resources management studies. This will certainly assist policy and decision-makers to establish strategies, priorities, and the proper use of water resources in the Sinú river watershed.

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Han, Qi, Kejia Zhu, Caibo Hu, He Zhao, Shuang Wu, and Yu Fu. "BOC Signal Acquisition Algorithm Based on Similar Enfoldment." International Journal of Aerospace Engineering 2020 (February 25, 2020): 1–19. http://dx.doi.org/10.1155/2020/4314132.

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A BOC signal has been widely used in the Global Navigation Satellite System (GNSS). Although the BOC signal has many advantages, the autocorrelation function (ACF) of the BOC signal has lots of peaks, which makes signal acquisition difficult. This paper proposes a similar enfoldment acquisition (SEA) algorithm, which can be applied to sin-BOC and cos-BOC signals, with even and odd modulation orders. The SEA algorithm utilizes the similarity between the main peak and the secondary peak to construct a new ACF to eliminate the ambiguity of the BOC signal. This paper simulates the acquisition performance of the SEA algorithm, Martin algorithm, and SCPC algorithm, while the simulation result shows that the SEA algorithm is superior to the Martin algorithm and SCPC algorithm. Since the SEA algorithm does not need filters or auxiliary signals, its complexity is lower than that of the Martin algorithm and SCPC algorithm.

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Avazov, Nurilla, and Matthias Pätzold. "Design of Wideband MIMO Car-to-Car Channel Models Based on the Geometrical Street Scattering Model." Modelling and Simulation in Engineering 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/264213.

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We propose a wideband multiple-input multiple-output (MIMO) car-to-car (C2C) channel model based on the geometrical street scattering model. Starting from the geometrical model, a MIMO reference channel model is derived under the assumption of single-bounce scattering in line-of-sight (LOS) and non-LOS (NLOS) propagation environments. The proposed channel model assumes an infinite number of scatterers, which are uniformly distributed in two rectangular areas located on both sides of the street. Analytical solutions are presented for the space-time-frequency cross-correlation function (STF-CCF), the two-dimensional (2D) space CCF, the time-frequency CCF (TF-CCF), the temporal autocorrelation function (ACF), and the frequency correlation function (FCF). An efficient sum-of-cisoids (SOCs) channel simulator is derived from the reference model. It is shown that the temporal ACF and the FCF of the SOC channel simulator fit very well to the corresponding correlation functions of the reference model. To validate the proposed channel model, the mean Doppler shift and the Doppler spread of the reference model have been matched to real-world measurement data. The comparison results demonstrate an excellent agreement between theory and measurements, which confirms the validity of the derived reference model. The proposed geometry-based channel simulator allows us to study the effect of nearby street scatterers on the performance of C2C communication systems.

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Hariri, A., J. W. Zu, and R. Ben Mrad. "n -Point Asperity Model for Contact Between Nominally Flat Surfaces." Journal of Tribology 128, no. 3 (March 10, 2006): 505–14. http://dx.doi.org/10.1115/1.2194915.

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For several decades, asperities of nominally flat rough surfaces were considered to be points higher than their immediate neighbors. Recently, it has been recognized that this model is incorrect. To address the issue, a new multiple-point asperity model, called the n-point asperity model, is introduced in this paper. In the new model, asperities are composed of n neighboring sampled points with n-2 middle points being above a certain level. When the separation between two surfaces decreases, new asperities with higher number of sample points, n, will come into existence. Based on the above model, the height and curvature of n-point asperities are defined and their distributions are found. The model is developed for Gaussian surfaces and for the general case of an autocorrelation function (ACF). As a case study, the exponential ACF is applied to the new model, which is shown to produce remarkably good agreement with measurements from real and simulated surfaces.

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Liu, Zhijun, Baiyu Li, Xiangwei Zhu, Lixun Li, and Guangfu Sun. "Band-Pass Sampling in High-Order BOC Signal Acquisition." Applied Sciences 8, no. 11 (November 12, 2018): 2226. http://dx.doi.org/10.3390/app8112226.

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The binary offset carrier (BOC) modulation, which has been adopted in modern global navigation satellite systems (GNSS), provides a higher spectral compatibility with BPSK signals, and better tracking performance. However, the autocorrelation function (ACF) of BOC signals has multiple peaks. This feature complicates the acquisition process, since a smaller time searching step is required, which results in longer searching time or greater amounts of hardware resources. Another problem is the high Nyquist frequency, which leads to high computational complexity and power consumption. In this paper, to overcome these drawbacks, the band-pass sampling technique for multiple signals is introduced to BOC signals. The sampling frequency can be reduced significantly. Furthermore, the ACF of the sampled signal has only two secondary peaks, so that the code phase can be searched with a larger searching step. An acquisition structure base on dual-loop is proposed, to completely eliminate the ambiguity and compensate the subcarrier Doppler. The acquisition performance and the computational complexity are also analysed.

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Alsharif, Mohammed, Mohammad Younes, and Jeong Kim. "Time Series ARIMA Model for Prediction of Daily and Monthly Average Global Solar Radiation: The Case Study of Seoul, South Korea." Symmetry 11, no. 2 (February 15, 2019): 240. http://dx.doi.org/10.3390/sym11020240.

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Forecasting solar radiation has recently become the focus of numerous researchers due to the growing interest in green energy. This study aims to develop a seasonal auto-regressive integrated moving average (SARIMA) model to predict the daily and monthly solar radiation in Seoul, South Korea based on the hourly solar radiation data obtained from the Korean Meteorological Administration over 37 years (1981–2017). The goodness of fit of the model was tested against standardized residuals, the autocorrelation function, and the partial autocorrelation function for residuals. Then, model performance was compared with Monte Carlo simulations by using root mean square errors and coefficient of determination (R2) for evaluation. In addition, forecasting was conducted by using the best models with historical data on average monthly and daily solar radiation. The contributions of this study can be summarized as follows: (i) a time series SARIMA model is implemented to forecast the daily and monthly solar radiation of Seoul, South Korea in consideration of the accuracy, suitability, adequacy, and timeliness of the collected data; (ii) the reliability, accuracy, suitability, and performance of the model are investigated relative to those of established tests, standardized residual, autocorrelation function (ACF), and partial autocorrelation function (PACF), and the results are compared with those forecasted by the Monte Carlo method; and (iii) the trend of monthly solar radiation in Seoul for the coming years is analyzed and compared on the basis of the solar radiation data obtained from KMS over 37 years. The results indicate that (1,1,2) the ARIMA model can be used to represent daily solar radiation, while the seasonal ARIMA (4,1,1) of 12 lags for both auto-regressive and moving average parts can be used to represent monthly solar radiation. According to the findings, the expected average monthly solar radiation ranges from 176 to 377 Wh/m2.

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Mahey, Rachna. "To investigate the Temporal and Spatial correlation behavioral characteristics of MIMO fading channels." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 14, no. 7 (May 15, 2015): 5895–910. http://dx.doi.org/10.24297/ijct.v14i7.1906.

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This paper deals with the analysis of performance bounds of narrowband multiple-input multiple-output (MIMO) fading channels considering the transmission links from the mobile station (MS) to the base station (BS) through non-line-of-sight (NLOS) propagation conditions. It is assumed that an infinite number of local scatterers surround the MS and the BS. The Temporal as well as Spatial correlation properties of channel models are explored along with their capacity. The effect of number of scatterers; Doppler frequency; and isotropic/non-isotropic scattering conditions, on MIMO channel models is investigated in terms of statistical properties of one ring and two ring models, i.e. Time Autocorrelation Function (ACF) and two-dimensional (2D) Space Cross-correlation Function (CCF).Â

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Hughson, R. L., L. A. Cuervo, A. E. Patla, D. A. Winter, H. C. Xing, B. H. Dietrich, and G. D. Swanson. "Time domain analysis of oxygen uptake during pseudorandom binary sequence exercise tests." Journal of Applied Physiology 71, no. 4 (October 1, 1991): 1620–26. http://dx.doi.org/10.1152/jappl.1991.71.4.1620.

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Pseudorandom binary sequence (PRBS) exercise tests involve repeated switching between two work rates (WR) according to a computer-generated pattern. This paper presents an approach to analysis of O2 uptake (VO2) in the time domain. First, the autocorrelation function (ACF) of the input WR was recognized to be a triangular-shaped pulse that can be taken to be equivalent to a ramp increase followed by a ramp decrease in WR. Then the cross-correlation function of the input (WR) and the output (VO2) was treated as if it were the response to a triangular-shaped pulse. The cross-correlation function was analyzed by fitting a linear summation of the ramp form of a two-component exponential function to this triangular pulse. VO2 responses of eight subjects were obtained from two different PRBS tests, as well as step changes in WR. The first PRBS test consisted of 15 units, each 30 s in duration. Its ACF had a base width of 60 s. The ramp increase-ramp decrease model fit the data throughout the range of response. The second PRBS test had 63 units, each 5 s in duration; thus its ACF base width was 10 s. Again, the ramp model fit adequately. The data from the second PRBS test could be fit by the impulse form of the two-component exponential equation, although the fit in the first 30 s tended to be poorer. The time constants of VO2 dynamics estimated from step and PRBS tests were not significantly different. PRBS tests can be analyzed in the time domain, and the indicators of system dynamics reflect physiological properties similar to those investigated during step changes in WR.

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Bécares, Eloy, Susana Romo, and Margarita Fernandez-Aláez. "Population dynamics using temporal series analysis in a industrial two-stage activated sludge pilot plant." Water Science and Technology 37, no. 4-5 (February 1, 1998): 255–58. http://dx.doi.org/10.2166/wst.1998.0638.

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A time series analysis using an autocorrelation function (ACF) was used to assess the relative importance of density (DD) and non density-dependent - (NDD) factors on microfauna abundance of a two-stage activated sludge pilot plant treating industrial effluents. Although some previous work has detected a carrying capacity for the total microfauna abundance in both reactors, ACF showed a general pattern of non-density dependent abundance regulation. Stationarity due to density-dependent factors was observed for the two major species in the first reactor, the sessile Opercularia asymmetrica and the crawling Chilodonatella minuta. There was no evidence of bacterial competition and only weak evidence of floc surface competition. It is possible that the main driving factor in the first reactor was the constant wasting rate. In the second reactor, the microfauna was clearly dependent on substrate fluctuations, attaining densities one order of magnitude higher than in the first reactor. This was probably a consequence of its longer sludge age. An 8-day oscillation period was detected only in the first reactor, while a second oscillation of about 30 days was observed in both the first and second reactors. ACF was shown to be a simple method for discriminating between DD and NDD factors influencing species and total abundance dynamics.

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Delignières, Didier. "Correlation Properties of (Discrete) Fractional Gaussian Noise and Fractional Brownian Motion." Mathematical Problems in Engineering 2015 (2015): 1–7. http://dx.doi.org/10.1155/2015/485623.

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The fractional Gaussian noise/fractional Brownian motion framework (fGn/fBm) has been widely used for modeling and interpreting physiological and behavioral data. The concept of 1/fnoise, reflecting a kind of optimal complexity in the underlying systems, is of central interest in this approach. It is generally considered that fGn and fBm represent a continuum, punctuated by the boundary of “ideal” 1/fnoise. In the present paper, we focus on the correlation properties of discrete-time versions of these processes (dfGn and dfBm). We especially derive a new analytical expression of the autocorrelation function (ACF) of dfBm. We analyze the limit behavior of dfGn and dfBm when they approach their upper and lower limits, respectively. We show that, asHapproaches 1, the ACF of dfGn tends towards 1 at all lags, suggesting that dfGn series tend towards straight line. Conversely, asHapproaches 0, the ACF of dfBm tends towards 0 at all lags, suggesting that dfBm series tend towards white noise. These results reveal a severe breakdown of correlation properties around the 1/fboundary and challenge the idea of a smooth transition between dfGn and dfBm processes. We discuss the implications of these findings for the application of the dfGn/dfBm model to experimental series, in terms of theoretical interpretation and modeling.

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Soeta, Yoshiharu, and Ei Onogawa. "Psycho-physiological evaluations of low-level impulsive sounds produced by air conditioners." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 263, no. 5 (August 1, 2021): 1186–93. http://dx.doi.org/10.3397/in-2021-1771.

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Air conditioners are widely used in buildings to maintain thermal comfort for long time. Air conditioners produce sounds during operation, and air conditioners are regarded as one of the main noise sources in buildings. Most sounds produced by the air conditioner do not fluctuate over time and sound quality of the steady sounds produced by the air conditioner have been evaluated. However, air conditioners sometimes produce low-level and impulsive sounds. Customers criticizes such sounds are annoying when they sleep and they spend time quietly in the living room. The aim of this study was to determine the factors that significantly influence the psycho-physiological response to the low-level impulsive sounds produced by air conditioners. We assessed the A-weighted equivalent continuous sound pressure level (LAeq) and factors extracted from the autocorrelation function (ACF). Subjective loudness, sharpness, annoyance, and electroencephalography (EEG) were evaluated. Multiple regression analyses were performed using a linear combination of LAeq, the ACF factors, and their standard deviations. The results indicated that LAeq, the delay time of the first maximum peak, the width of the first decay of the ACF, and the magnitude and width of the IACF could predict psycho-physiological responses to air conditioner sounds.

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Jiang, Kaili, Xiaomin Chen, Qiuming Zhu, Lele Chen, Dazhuan Xu, and Bing Chen. "A Novel Simulation Model for Nonstationary Rice Fading Channels." Wireless Communications and Mobile Computing 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/8086073.

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In this paper, we propose a new simulator for nonstationary Rice fading channels under nonisotropic scattering scenarios, as well as the improved computation method of simulation parameters. The new simulator can also be applied on generating Rayleigh fading channels by adjusting parameters. The proposed simulator takes into account the smooth transition of fading phases between the adjacent channel states. The time-variant statistical properties of the proposed simulator, that is, the probability density functions (PDFs) of envelope and phase, autocorrelation function (ACF), and Doppler power spectrum density (DPSD), are also analyzed and derived. Simulation results have demonstrated that our proposed simulator provides good approximation on the statistical properties with the corresponding theoretical ones, which indicates its usefulness for the performance evaluation and validation of the wireless communication systems under nonstationary and nonisotropic scenarios.

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Sun, Xiyan, Shaojie Song, Yuanfa Ji, Xingli Gan, Suqing Yan, and Xizi Jia. "An Unambiguous Synchronization Scheme for GNSS BOC Signals Based on Reconstructed Correlation Function." Sensors 21, no. 6 (March 11, 2021): 1982. http://dx.doi.org/10.3390/s21061982.

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Binary offset carrier (BOC) modulation is a new modulation method that has been gradually applied to the Global Satellite Navigation System (GNSS) in recent years. However, due to the multi-peaks in its auto-correlation function (ACF), it will incur a false lock and generate synchronization ambiguous potentially. In this paper, an unambiguous synchronization method based on a reconstructed correlation function is proposed to solve the ambiguity problem. First, through the shape code vector constructed in this paper, the general cross-correlation function (CCF) expression of the BOC modulated signal will be obtained. Based on the features of the signal correlation function, it is decomposed into a matrix form of trigonometric functions. Then, it generates two local signal waves using a specific method, then the proposed method is implemented to obtain a no-side-peak correlation function by reconstructing the cross-correlation between the received signal and the two local signals. Simulations showed that it fully eliminates the side-peak threat and significantly removes the ambiguity during the synchronization of the BOC signals. This paper also gives the improved structure of acquisition and tracking. The detailed theoretical deduction of detection probability and code tracking error is demonstrated, and the corresponding phase discrimination function is given. In terms of de-blurring ability and detection probability performance, the proposed method outperformed other conventional approaches. The tracking performance was superior to the comparison methods and the phase discrimination curve only had a zero-crossing, which successfully removed the false lock points. In addition, in multipath mitigation, it outperformed the ACF of the BOC signal, and performs as well as the autocorrelation side-peak cancellation technique (ASPeCT) for BOC(kn,n) signals.

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Huang, Xiaoqian, Weiping Ma, Chikin Law, Jianfeng Luo, and Naiqing Zhao. "Importance of applying Mixed Generalized Additive Model (MGAM) as a method for assessing the environmental health impacts: Ambient temperature and Acute Myocardial Infarction (AMI), among elderly in Shanghai, China." PLOS ONE 16, no. 8 (August 12, 2021): e0255767. http://dx.doi.org/10.1371/journal.pone.0255767.

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Association between acute myocardial infarction (AMI) morbidity and ambient temperature has been examined with generalized linear model (GLM) or generalized additive model (GAM). However, the effect size by these two methods might be biased due to the autocorrelation of time series data and arbitrary selection of degree of freedom of natural cubic splines. The present study analyzed how the climatic factors affected AMI morbidity for older adults in Shanghai with Mixed generalized additive model (MGAM) that addressed these shortcomings mentioned. Autoregressive random effect was used to model the relationship between AMI and temperature, PM10, week days and time. The degree of freedom of time was chosen based on the seasonal pattern of temperature. The performance of MGAM was compared with GAM on autocorrelation function (ACF), partial autocorrelation function (PACF) and goodness of fit. One-year predictions of AMI counts in 2011 were conducted using MGAM with the moving average. Between 2007 and 2011, MGAM adjusted the autocorrelation of AMI time series and captured the seasonal pattern after choosing the degree of freedom of time at 5. Using MGAM, results were well fitted with data in terms of both internal (R2 = 0.86) and external validity (correlation coefficient = 0.85). The risk of AMI was relatively high in low temperature (Risk ratio = 0.988 (95% CI 0.984, 0.993) for under 12°C) and decreased as temperature increased and speeded up within the temperature zone from 12°C to 26°C (Risk ratio = 0.975 (95% CI 0.971, 0.979), but it become increasing again when it is 26°C although not significantly (Risk ratio = 0.999 (95% CI 0.986, 1.012). MGAM is more appropriate than GAM in the scenario of response variable with autocorrelation and predictors with seasonal variation. The risk of AMI was comparatively higher when temperature was lower than 12°C in Shanghai as a typical representative location of subtropical climate.

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Kumar, Varun, Abhay Singh, Mrinmoy Adhikary, Shailaja Daral, Anita Khokhar, and Saudan Singh. "Seasonality of Tuberculosis in Delhi, India: A Time Series Analysis." Tuberculosis Research and Treatment 2014 (2014): 1–5. http://dx.doi.org/10.1155/2014/514093.

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Background. It is highly cost effective to detect a seasonal trend in tuberculosis in order to optimize disease control and intervention. Although seasonal variation of tuberculosis has been reported from different parts of the world, no definite and consistent pattern has been observed. Therefore, the study was designed to find the seasonal variation of tuberculosis in Delhi, India.Methods. Retrospective record based study was undertaken in a Directly Observed Treatment Short course (DOTS) centre located in the south district of Delhi. Six-year data from January 2007 to December 2012 was analyzed. Expert modeler of SPSS ver. 21 software was used to fit the best suitable model for the time series data.Results. Autocorrelation function (ACF) and partial autocorrelation function (PACF) at lag 12 show significant peak suggesting seasonal component of the TB series. Seasonal adjusted factor (SAF) showed peak seasonal variation from March to May. Univariate model by expert modeler in the SPSS showed that Winter’s multiplicative model could best predict the time series data with 69.8% variability. The forecast shows declining trend with seasonality.Conclusion. A seasonal pattern and declining trend with variable amplitudes of fluctuation were observed in the incidence of tuberculosis.

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Hariri, A., J. W. Zu, and R. Ben Mrad. "Modeling of Elastic/Plastic Contact Between Nominally Flat Rough Surfaces Using an n-Point Asperity Model." Journal of Tribology 128, no. 4 (May 3, 2006): 876–85. http://dx.doi.org/10.1115/1.2345409.

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The asperities of rough surfaces have long been considered to be points higher than their immediate neighbors. Based on this concept, theories were developed for quantitatively understanding the elastic and plastic nature of contact between rough surfaces. Recently it has been recognized that the above model for asperities is inadequate. Consequently, all the models that have been constructed based on that model are inadequate too. In this paper, based on a newly developed multiple-point asperity model, the elastic and plastic contact problem between nominally flat surfaces is reformulated. This leads to finding the deformed area, and load produced by the contact. The model is developed for the general form of isotropic rough surfaces with arbitrary height distribution and autocorrelation function (ACF). The microcontact areas generated by each asperity contact are considered to be circles. The Gaussian distribution of heights and exponential ACF are considered as a benchmark to compare the results of the new model with the existing models. Using results from numerical models developed by other groups, the new model is validated.

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Hsu, Fengchi, Mikhail Zhizhin, Tilottama Ghosh, Christopher Elvidge, and Jay Taneja. "The Annual Cycling of Nighttime Lights in India." Remote Sensing 13, no. 6 (March 21, 2021): 1199. http://dx.doi.org/10.3390/rs13061199.

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India is known to have unstable power supply, and many locations show an annual cycle in VIIRS Nighttime Light (VNL). In this study, autocorrelation function (ACF) analysis is used to identify the annual cycling in VNL. Two fundamentally different classification techniques are proposed to classify the ACF profile into one of the three arch types, i.e., acyclic, single peak, and dual peak. The results from the two classification techniques are closely compared to verify their output. This analysis is carried out for the entire territory of India in 15 arc second grid cells. The power stability data acquired from the India Human Development Survey (IHDS) and the Electricity Supply Monitoring Initiative (ESMI) are used to verify their relationship to the annual cycling of VNL. To further aide the analysis, land use/land class are accounted for by data from the India National Remote Sensing Center (NRSC). As a result, the contribution of power stability to VNL annual cycling in India is inconclusive due to the limitation of power stability data. Furthermore, other potential factors should be further examined.

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Archer, Michael. "The social wasp Vespula germanica (Fabricius) (Hymenoptera: Vespidae) population dynamics in England over 39 years." Entomologist's Monthly Magazine 154, no. 2 (April 28, 2018): 149–55. http://dx.doi.org/10.31184/m00138908.1542.3906.

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1. Yearly records of worker Vespula germanica (Fabricius) taken in suction traps at Silwood Park (28 years) and at Rothamsted Research (39 years) are examined. 2. Using the autocorrelation function (ACF), a significant negative 1-year lag followed by a lesser non-significant positive 2-year lag was found in all, or parts of, each data set, indicating an underlying population dynamic of a 2-year cycle with a damped waveform. 3. The minimum number of years before the 2-year cycle with damped waveform was shown varied between 17 and 26, or was not found in some data sets. 4. Ecological factors delaying or preventing the occurrence of the 2-year cycle are considered.

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Tripathi, Rahul, A. K. Nayak, R. Raja, Mohammad Shahid, Anjani Kumar, Sangita Mohanty, B. B. Panda, B. Lal, and Priyanka Gautam. "Forecasting Rice Productivity and Production of Odisha, India, Using Autoregressive Integrated Moving Average Models." Advances in Agriculture 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/621313.

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Forecasting of rice area, production, and productivity of Odisha was made from the historical data of 1950-51 to 2008-09 by using univariate autoregressive integrated moving average (ARIMA) models and was compared with the forecasted all Indian data. The autoregressive (p) and moving average (q) parameters were identified based on the significant spikes in the plots of partial autocorrelation function (PACF) and autocorrelation function (ACF) of the different time series. ARIMA (2, 1, 0) model was found suitable for all Indian rice productivity and production, whereas ARIMA (1, 1, 1) was best fitted for forecasting of rice productivity and production in Odisha. Prediction was made for the immediate next three years, that is, 2007-08, 2008-09, and 2009-10, using the best fitted ARIMA models based on minimum value of the selection criterion, that is, Akaike information criteria (AIC) and Schwarz-Bayesian information criteria (SBC). The performances of models were validated by comparing with percentage deviation from the actual values and mean absolute percent error (MAPE), which was found to be 0.61 and 2.99% for the area under rice in Odisha and India, respectively. Similarly for prediction of rice production and productivity in Odisha and India, the MAPE was found to be less than 6%.

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Agboola, S., P. Niyang, O. Olawepo, W. Ukponu, S. Niyang, I. Ujata, A. Ihueze, et al. "Forecasting the spread and total size of confirmed and discharged cases of COVID-19 in Nigeria using an ARIMA model." Statistical Journal of the IAOS 37, no. 2 (June 3, 2021): 517–22. http://dx.doi.org/10.3233/sji-200758.

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Coronavirus disease 2019 (COVID-19) has been considered a global threat spreading to Nigeria and posing major public health threats and concerns. This led to the introduction of internationally acceptable non-pharmaceutical interventions (NPI) such as lockdowns, social distancing, and mandatory use of face masks by the Nigerian government to curtail the disease. This study aims to develop an Autoregressive Integrated Moving Average (ARIMA) model to predict COVID-19 cases vis Total Confirmed Cases (TCC) and Total Discharged Cases (TDC) in Nigeria based on the daily data obtained from the Nigeria Centre for Diseases Control (NCDC) from 27th February 2020 to 6th June 2020. The autocorrelation function (ACF), and partial autocorrelation function (PACF) were used to determine the constructed model. An ARIMA model was developed to predict the trend of TCC and TDC for the next 200 days. Forecasting was done using the constructed models. The finding shown that TCC increased to 50,225 with a CI between 29,425 to 100,450 and TDC to 20,186 with CI between 11,106 to 40,366 approximately. The result shows a significant increase in both TCC and TDC from COVID-19 which should guide the government roll out and management of the different NPI and policies to contain the virus.

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Ren, Zhicheng, Fangqi Zhang, Guoxin Zheng, Asad Saleem, and Ke Guan. "A 3D Non-Stationary Channel Model with Moving Mobile Station in Rectangular Tunnel." International Journal of Antennas and Propagation 2019 (May 2, 2019): 1–12. http://dx.doi.org/10.1155/2019/6750153.

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This paper presents a three-dimensional (3D) geometry-based stochastic model (GBSM) for capturing the non-stationarity of radio channel at 1.8 GHz in a rectangular tunnel. A time-variant (TV) complex channel gain is derived for obtaining the statistical properties in time, frequency, and spatial domains such as the time-variant autocorrelation function (TV-ACF), the time-variant Doppler power spectral density (TV-DPSD), and the time-variant spatial cross-correlation function (TV-CCF), respectively. Then the TV channel statistical properties at different time instants can be extracted and the non-stationary channel characteristics caused by the TV scattering environment are thoroughly discussed. Furthermore, three cases including “approach”, “arrival”, and “away” are set to allow a comprehensive study on how the DPSD behaves with the relative position between transmitter and receiver. The reliability of proposed 3D GBSM is highlighted by a good agreement with the measured result in terms of the correlation function.

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Journal articles on the topic 'Autocorrelation function (ACF)'

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