Academic literature on the topic 'Waveform generation algorithms'
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Journal articles on the topic "Waveform generation algorithms"
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Oliveira, Andrey Augusto Alves de, Jorge Antonio Silva Centeno, and Fabiano Scheer Hainosz. "POINT CLOUD GENERATION FROM GAUSSIAN DECOMPOSITION OF THE WAVEFORM LASER SIGNAL WITH GENETIC ALGORITHMS." Boletim de Ciências Geodésicas 24, no. 2 (June 2018): 270–87. http://dx.doi.org/10.1590/s1982-21702018000200018.
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Abstract: Recent developments in LIDAR technology lead to the availability of the waveform systems, which capture and digitize the whole return of the emitted LASER pulse. As many objects may cause multiple returns in the same echo, one task is to detect and separate different echoes within the same digitized measurement. In this paper the results of a study aimed at LASER signal waveform decomposition using genetic algorithms are introduced. The proposed method is based on the Gaussian decomposition approach and analyzes each digitized return to compute one or more points. Initially, the number of peaks contained in the waveform is determined by a simple peak detection method, with a local maximum point algorithm. When more than one peak is detected, genetic algorithms are applied to estimate the amplitude, time and standard deviation of each peak within the digitized signal. With this methodology it was possible to increase the number of points by approximately 17 % compared to the point cloud obtained using commercial software. The best results were obtained in areas with high vegetation, and thus the methodology can be applied to the generation of denser points cloud in forest areas.
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Sui, Jingkun, Qingcai Zeng, Zhifang Yang, Xiaodong Zheng, and Tianyue Hu. "Amplitude semblance and its fusion with the third-generation coherence for characterization of fractured-vuggy carbonate reservoirs." Journal of Geophysics and Engineering 19, no. 5 (September 10, 2022): 1005–11. http://dx.doi.org/10.1093/jge/gxac061.
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Abstract In the Tarim Basin, the main hydrocarbon reservoirs of Ordovician carbonate rocks are fractured-vuggy reservoirs, of which the underground river type reservoirs are an important type. Seismic coherence attribute can highlight seismic discontinuity caused by tectonic movements, reservoir boundaries, sedimentary body boundaries or other factors. Thus, it is a widely used key technique in seismic interpretation. There are many algorithms to determine the coherence. Typically, the coherence algorithm based on eigen-structure analysis is the most robust, but is sensitive to waveform differences and insensitive to amplitude differences. This paper proposes an amplitude coherence attribute to measure semblance of root-mean-square (RMS) amplitudes of multiple traces and fuses it with the third-generation coherence (C3) to describe the boundary of underground river. Model test and case study prove that the proposed fused algorithm can effectively identify the amplitude and waveform differences in seismic data.
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Younis, Raneen, and Andreas Reinhardt. "A Study on Fundamental Waveform Shapes in Microscopic Electrical Load Signatures." Energies 13, no. 12 (June 12, 2020): 3039. http://dx.doi.org/10.3390/en13123039.
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The number of globally deployed smart meters is rising, and so are the sampling rates at which they can meter electrical consumption data. As a consequence thereof, the technological foundation is established to track the power intake of buildings at sampling rates up to several k Hz . Processing raw signal waveforms at such rates, however, imposes a high resource demand on the metering devices and data processing algorithms alike. In fact, the ensuing resource demand often exceeds the capabilities of the embedded systems present in current-generation smart meters. Consequently, the majority of today’s energy data processing algorithms are confined to the use of RMS values of the data instead, reported once per second or even less frequently. This entirely eliminates the spectral characteristics of the signal waveform (i.e., waveform trajectories of electrical voltage, current, or power) from the data, despite the wealth of information they have been shown to contain about the operational states of the operative appliances. In order to overcome this limitation, we pursue a novel approach to handle the ensuing volume of load signature data and simultaneously facilitate their analysis. Our proposed method is based on approximating the current intake of electrical appliances by means of parametric models, the determination of whose parameters only requires little computational power. Through the identification of model parameters from raw measurements, smart meters not only need to transmit less data, but the identification of individual loads in aggregate load signature data is facilitated at the same time. We conduct an analysis of the fundamental waveform shapes prevalent in the electrical power consumption data of more than 50 electrical appliances, and assess the induced approximation errors when replacing raw current consumption data by parametric models. Our results show that the current consumption of many household appliances can be accurately modeled by a small number of parameterizable waveforms.
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Witte, Philipp A., Mathias Louboutin, Navjot Kukreja, Fabio Luporini, Michael Lange, Gerard J. Gorman, and Felix J. Herrmann. "A large-scale framework for symbolic implementations of seismic inversion algorithms in Julia." GEOPHYSICS 84, no. 3 (May 1, 2019): F57—F71. http://dx.doi.org/10.1190/geo2018-0174.1.
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Writing software packages for seismic inversion is a very challenging task because problems such as full-waveform inversion or least-squares imaging are algorithmically and computationally demanding due to the large number of unknown parameters and the fact that waves are propagated over many wavelengths. Therefore, software frameworks need to combine versatility and performance to provide geophysicists with the means and flexibility to implement complex algorithms that scale to exceedingly large 3D problems. Following these principles, we have developed the Julia Devito Inversion framework, an open-source software package in Julia for large-scale seismic modeling and inversion based on Devito, a domain-specific language compiler for automatic code generation. The framework consists of matrix-free linear operators for implementing seismic inversion algorithms that closely resemble the mathematical notation, a flexible resilient parallelization, and an interface to Devito for generating optimized stencil code to solve the underlying wave equations. In comparison with many manually optimized industry codes written in low-level languages, our software is built on the idea of independent layers of abstractions and user interfaces with symbolic operators. Through a series of numerical examples, we determined that this allows users to implement a series of increasingly complex algorithms for waveform inversion and imaging as simple Julia scripts that scale to large-scale 3D problems. This illustrates that software based on the paradigms of abstract user interfaces and automatic code generation and makes it possible to manage the complexity of the algorithms and performance optimizations, thus providing a high-performance research and production framework.
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Stoffa, Paul L., and Mrinal K. Sen. "Nonlinear multiparameter optimization using genetic algorithms: Inversion of plane‐wave seismograms." GEOPHYSICS 56, no. 11 (November 1991): 1794–810. http://dx.doi.org/10.1190/1.1442992.
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Seismic waveform inversion is one of many geophysical problems which can be identified as a nonlinear multiparameter optimization problem. Methods based on local linearization fail if the starting model is too far from the true model. We have investigated the applicability of “Genetic Algorithms” (GA) to the inversion of plane‐wave seismograms. Like simulated annealing, genetic algorithms use a random walk in model space and a transition probability rule to help guide their search. However, unlike a single simulated annealing run, the genetic algorithms search from a randomly chosen population of models (strings) and work with a binary coding of the model parameter set. Unlike a pure random search, such as in a “Monte Carlo” method, the search used in genetic algorithms is not directionless. Genetic algorithms essentially consist of three operations, selection, crossover, and mutation, which involve random number generation, string copies, and some partial string exchanges. The choice of the initial population, the probabilities of crossover and mutation are crucial for the practical implementation of the algorithm. We investigated the effects of these parameters in the inversion of plane‐wave seismograms in which a normalized crosscorrelation function was used as the objective or fitness function (E). We also introduce the concept of “update” probability to control the influence of past generations. The combination of a low value of mutation probability (∼0.01), a moderate value of the crossover probability (∼0.6) and a high value of update probability (∼0.9) are found to be optimal for the convergence of the algorithm. Further, we show that concepts from simulated annealing can be used effectively for the stretching of the fitness function which helps in the convergence of the algorithm. Thus, we propose to use exp (E/T) rather than E as the fitness function, where T (analogous to temperature in simulated annealing) is a properly chosen parameter which can change slowly with each generation. Also, by repeating the GA optimization procedure several times with different randomly chosen initial model populations, we derive “a very good subset” of models from the entire model space and calculate the a posteriori probability density σ(m) ∝ exp (E(m)/T). The σ(m) ’s are then used to calculate a “mean” model, which is found to be close to the true model.
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Bellan, Diego, and Sergio A. Pignari. "Statistical Properties of Real–Time Amplitude Estimate of Harmonics Affected by Frequency Instability." Journal of Electrical Engineering 67, no. 4 (July 1, 2016): 292–98. http://dx.doi.org/10.1515/jee-2016-0043.
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Abstract This work deals with the statistical characterization of real-time digital measurement of the amplitude of harmonics affected by frequency instability. In fact, in modern power systems both the presence of harmonics and frequency instability are well-known and widespread phenomena mainly due to nonlinear loads and distributed generation, respectively. As a result, real-time monitoring of voltage/current frequency spectra is of paramount importance as far as power quality issues are addressed. Within this framework, a key point is that in many cases real-time continuous monitoring prevents the application of sophisticated algorithms to extract all the information from the digitized waveforms because of the required computational burden. In those cases only simple evaluations such as peak search of discrete Fourier transform are implemented. It is well known, however, that a slight change in waveform frequency results in lack of sampling synchronism and uncertainty in amplitude estimate. Of course the impact of this phenomenon increases with the order of the harmonic to be measured. In this paper an approximate analytical approach is proposed in order to describe the statistical properties of the measured magnitude of harmonics affected by frequency instability. By providing a simplified description of the frequency behavior of the windows used against spectral leakage, analytical expressions for mean value, variance, cumulative distribution function, and probability density function of the measured harmonics magnitude are derived in closed form as functions of waveform frequency treated as a random variable.
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Spurio Mancini, Alessio, Davide Piras, Ana Margarida Godinho Ferreira, Michael Paul Hobson, and Benjamin Joachimi. "Accelerating Bayesian microseismic event location with deep learning." Solid Earth 12, no. 7 (July 29, 2021): 1683–705. http://dx.doi.org/10.5194/se-12-1683-2021.
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Abstract. We present a series of new open-source deep-learning algorithms to accelerate Bayesian full-waveform point source inversion of microseismic events. Inferring the joint posterior probability distribution of moment tensor components and source location is key for rigorous uncertainty quantification. However, the inference process requires forward modelling of microseismic traces for each set of parameters explored by the sampling algorithm, which makes the inference very computationally intensive. In this paper we focus on accelerating this process by training deep-learning models to learn the mapping between source location and seismic traces for a given 3D heterogeneous velocity model and a fixed isotropic moment tensor for the sources. These trained emulators replace the expensive solution of the elastic wave equation in the inference process. We compare our results with a previous study that used emulators based on Gaussian processes to invert microseismic events. For fairness of comparison, we train our emulators on the same microseismic traces and using the same geophysical setting. We show that all of our models provide more accurate predictions, ∼ 100 times faster predictions than the method based on Gaussian processes, and a 𝒪(105) speed-up factor over a pseudo-spectral method for waveform generation. For example, a 2 s long synthetic trace can be generated in ∼ 10 ms on a common laptop processor, instead of ∼ 1 h using a pseudo-spectral method on a high-profile graphics processing unit card. We also show that our inference results are in excellent agreement with those obtained from traditional location methods based on travel time estimates. The speed, accuracy, and scalability of our open-source deep-learning models pave the way for extensions of these emulators to generic source mechanisms and application to joint Bayesian inversion of moment tensor components and source location using full waveforms.
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Aboltins, Arturs, Dmitrijs Pikulins, Juris Grizans, and Sergejs Tjukovs. "Piscivorous Bird Deterrent Device Based on a Direct Digital Synthesis of Acoustic Signals." Elektronika ir Elektrotechnika 27, no. 6 (December 14, 2021): 42–48. http://dx.doi.org/10.5755/j02.eie.28977.
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This paper addresses the development of an acoustic deterrent device for the protection of fishponds and other objects against the unwanted presence of birds. The objective of the paper is not only providing of a deep analysis of available technologies for waveform synthesis and generation, but also building a theoretical base for the design and implementation of acoustic bird deterrent solutions. The paper addresses the synthesis of bird songs and calls using technologies for music, speech, and other types of acoustic signal processing. The second part of the paper is devoted to the unique algorithms and implementation details of the intelligent acoustic deterrence device prototype. The practical applicability of algorithms for bird call record conversion into synthesizer sequences has been analysed and possible issues are highlighted. The effectiveness and ease of practical implementation of the given method in the hardware are briefly discussed.
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Xia, Yuhao, Shilong Xu, Jiajie Fang, Ahui Hou, Youlong Chen, Xinyuan Zhang, and Yihua Hu. "A Novel Waveform Decomposition and Spectral Extraction Method for 101-Channel Hyperspectral LiDAR." Remote Sensing 14, no. 21 (October 22, 2022): 5285. http://dx.doi.org/10.3390/rs14215285.
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The 101-channel full-waveform hyperspectral LiDAR (FWHSL) is able to simultaneously obtain geometric and spectral information of the target, and it is widely applied in 3D point cloud terrain generation and classification, vegetation detection, automatic driving, and other fields. Currently, most waveform data processing methods are mainly aimed at single or several wavelengths. Hidden components are revealed mainly through optimization algorithms and comparisons of neighbor distance in different wavelengths. The same target may be misjudged as different ones when dealing with 101 channels. However, using the gain decomposition method with dozens of wavelengths will change the spectral intensity and affect the classification. In this paper, for hundred-channel FWHSL data, we propose a method that can detect and re-decompose the channels with outliers by checking neighbor distances and selecting specific wavelengths to compose a characteristic spectrum by performing PCA and clustering on the decomposition results for object identification. The experimental results show that compared with the conventional single channel waveform decomposition method, the average accuracy is increased by 20.1%, the average relative error of adjacent target distance is reduced from 0.1253 to 0.0037, and the degree of distance dispersion is reduced by 95.36%. The extracted spectrum can effectively characterize and distinguish the target and contains commonly used wavelengths that make up the vegetation index (e.g., 670 nm, 784 nm, etc.).
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Silva-Castro, Jhon. "A different methodology to control and predict ground vibrations from mine blasting." Canadian Geotechnical Journal 56, no. 7 (July 2019): 929–41. http://dx.doi.org/10.1139/cgj-2018-0073.
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Ground vibration prediction and control from mine blasting is a complex task involving disciplines such as geotechnical engineering, explosives engineering, and geology. Despite the importance of controlling ground vibrations, the mining industry commonly uses empirical methodologies based on concepts related to the nuclear tests era (charge weight scaling relationships). Over the past decade, attempts have been made to popularize more elaborate methodologies. These methods range from basic waveform superposition to analytical and numerical methods. Such methodologies are difficult to utilize daily because of their complexity, sometimes low accuracy (despite their sophistication), requirement for difficult to obtain parameters, and time needed to reach solutions using complex algorithms. In this paper, a different methodology to control and predict ground vibrations from blasting is presented. This methodology uses a semi-empirical approach, where the generation and propagation of ground vibration waves and the ground vibration characteristics at a point of interest are considered through the collection of a signature waveform. The methodology allows assessment of the optimum delay between charges to minimize and control ground vibration levels. A case study is included to demonstrate the benefits and the methodology in detail.
Dissertations / Theses on the topic "Waveform generation algorithms"
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Nehl, Albert Henry. "Investigation of techniques for high speed CMOS arbitrary waveform generation." PDXScholar, 1990. https://pdxscholar.library.pdx.edu/open_access_etds/4109.
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Today a growing number of applications in design engineering, production and environmental testing, and system service require specific analog waveforms and digital patterns. Such requirements are neither satisfactorily nor easily met by the use of standard function or single purpose, custom generators.
Traditional methods of waveform generation suffer from undesirable complexity or mediocre performance and are otherwise limited. For the majority of arbitrary waveform generation applications, including medical engineering, modal analysis and electronic engineering, direct digital synthesis techniques are satisfactory. Direct digital synthesis, based generally on periodic retrieval of predetermined amplitude values, may be used to 2 generate such waveforms. Within the limits imposed by the system's maximum sample rate and the Nyquist criteria, any waveform may be produced using these techniques.
The objective of this inquiry, within a particular set of constraints, is to extend the cost/performance envelope of direct digital synthesis techniques for the generation of arbitrary waveforms. Performance is enhanced, particularly in the areas of output bandwidth and signal purity.
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Fernández, Vicente Juan. "Reconfigurable Reflective Arrayed Waveguide Grating on Silicon Nitride." Doctoral thesis, Universitat Politècnica de València, 2021. http://hdl.handle.net/10251/165783.
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[ES] La presente tesis se ha centrado en el modelado, diseño y demonstración experimental por primera vez del dispositivo Reconfigurable Reflective Arrayed Waveguide Grating (R-RAWG). Para la consecución de este dispositivo que tiene posibilidades de uso en la espectrometría, una plataforma de nitruro de silicio llamada CNM-VLC se ha usado, ya que este material permite operar en un gran ancho de banda. Esta plataforma posee ciertas limitaciones y los elementos necesarios para el funcionamiento de este dispositivo tenían un performance bajo. Por ello, se ha desarrollado y validado una metodología que ha permitido obtener mejores divisores. Además, se ha diseñado un inverted taper que ha mejorado considerablemente el acoplo de luz al chip. Esto ha sido gracias a un exhaustivo análisis de opciones existentes en la literatura que también ha permitido escoger la mejor opción para realizar un espejo reconfigurable en la plataforma sin cambiar ni añadir ningún proceso de fabricación. Se han demostrado espejos reconfigurables gracias a utilizar divisores ópticos realimentados y también se ha desarrollado códigos que predicen el comportamiento del dispositivo experimentalmente. Con todo el trabajo realizado, se ha diseñado un R-RAWG para que pudiera operar en un gran ancho de banda y que los actuadores de fase no tuvieran peligro de estropearse. También se ha desarrollado un código para el modelado del R-RAWG que permite imitar la fabricación de estos dispositivos y que, gracias a esto, se ha desarrollado un método o algoritmo llamado DPASTOR, que usa algoritmos usados en machine learning, para optimizar la respuesta con tan sólo la potencia óptica de salida. Finalmente, se ha diseñado una PCB para poder conectar eléctricamente el chip fotónico y se ha desarrollado un método de medida que ha permitido tener una respuesta estable consiguiendo demostrar multitud de respuestas de filtros ópticos con el mismo dispositivo.[CAT] La present tesi s'ha centrat en el modelatge, disseny i demonstració experimental per primera vegada del dispositiu Reconfigurable Reflective Arrayed Waveguide Grating (R-RAWG). Per a la consecució d'aquest dispositiu que té possibilitats d'ús en l'espectrometria, una plataforma de nitrur de silici anomenada CNM-VLC s'ha usat ja que aquest material permet operar en una gran amplada de banda. Aquesta plataforma posseeix certes limitacions i els elements necessaris per al funcionament d'aquest dispositiu tenien un performance baix. Per això, s'ha desenvolupat i validat una metodologia que ha permés obtindre millors divisors i també, gràcies als processos de fabricació, s'ha dissenyat un acoplador que ha millorat considerablement l'acoble de llum al xip. Això ha sigut gràcies a un exhaustiu analisis d'opcions existents en la literatura que també ha permés triar la millor opció per a realitzar un espill reconfigurable en la plataforma sense canviar ni afegir cap procés de fabricació. S'han demonstrat espills reconfigurables gràcies a utilitzar divisors realimentats i també s'ha desenvolupat codis que prediuen el comportament del dispostiu experimentalment. Amb tot el treball realitzat, s'ha dissenyat un R-RAWG fent ús de determinades consideracions perquè poguera operar en una gran amplada de banda i que els actuadors de fase no tingueren perill de desbaratar-se. També s'ha desenvolupat un codi per al modelatge del R-RAWG que permet imitar la fabricació d'aquests dispositius i que, gràcies a això, s'ha desenvolupat un mètode o algorisme anomenat DPASTOR, que usa algorismes usats en machine learning, per a optimitzar la resposta amb tan sols la potència òptica d'eixida. Finalment, s'ha dissenyat una PCB per a poder connectar elèctricament el xip fotònic i s'ha desenvolupat un mètode de mesura que ha permés tindre una resposta estable aconseguint demostrar multitud de respostes de filtres òptics amb el mateix dispositiu.
[EN] This thesis is focused on the modelling, design and experimental demonstration for the first time of Reconfigurable Reflective Arrayed Waveguide Grating (R-RAWG) device. In order to build this device, that can be employed in spectrometry, a silicon nitride platform termed CNM-VLC has been chosen since this material allows to operate in broad range of wavelengths. This platform has the necessary elements, but some limitations because the operation of this device had a low performance. Therefore, a methodology has been developed and validated, which has allowed to obtain better splitters. Also an inverted taper has been designed, which has considerably improved the coupling of light to the chip. This has been possible thanks to an exhaustive analysis of existing options in the literature, that has allowed choosing the best option to make a reconfigurable mirror on the platform without changing or adding new manufacturing steps. Reconfigurable mirrors have been demonstrated by using feedback splitters. Furthermore, codes have been developed to predict the behaviour of the actual device. With all the work done, a R-RAWG has been designed by using certain considerations so that it can operate over a broad wavelength range and the phase actuators are not in danger of being damaged. A code has also been developed for the modelling of the R-RAWG, which allows manufacturing imperfections to be considered, thanks to this, a method or algorithm called DPASTOR has been developed. DPASTOR resembles machine learning to optimise the response by just using the optical output power. Finally, a PCB and an assembly with the chip interconnected to it have been made and designed. Moreover, a measurement method has been developed, which has made it possible to have a stable response and to demonstrate a multitude of optical filter responses with the same device.
Fernández Vicente, J. (2021). Reconfigurable Reflective Arrayed Waveguide Grating on Silicon Nitride [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/165783
TESIS
Book chapters on the topic "Waveform generation algorithms"
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Roja Reddy, B., and M. Uttara Kumari. "Generation of Orthogonal Discrete Frequency Coded Waveform Using Accelerated Particle Swarm Optimization Algorithm for MIMO Radar." In Advances in Intelligent and Soft Computing, 13–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-30157-5_2.
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Elavel Visuvanathan. G and Jaya. T. "A Novel Approach to Evaluate Reduced Inter Symbol Interference in UFMC Systems." In Advances in Parallel Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210071.
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The UFMC modulation scheme has been proposed as a solid competitive framework for future portable fifth generation communication. UFMC can be considered as a candidate waveform for 5G communications since it gives strength against Inter Symbol Interference (ISI) [1]. Inter-symbol interference prompted error can make the receiver neglect to reproduce the original data. Equalizers in the receivers, which are extraordinary sorts of filters, moderate the direct twisting created by the channel [2]. On the off chance that the channel’s time-fluctuating qualities are known from the earlier, at that point, the ideal setting for equalizers can be worked out. But in practical systems the channel’s time-changing attributes are not known from the earlier, so adaptive equalization method is applied in this paper based on the LMS algorithms. Adaptive equalizers are adjusted, or change the estimation of its taps as time advances [3].
Conference papers on the topic "Waveform generation algorithms"
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Wakabayashi, Kazuyuki, Takafumi Yamada, Satoshi Uemori, Osamu Kobayashi, Keisuke Kato, Haruo Kobayashi, Kiichi Niitsu, et al. "Low-Distortion Single-Tone and Two-Tone Sinewave Generation Algorithms Using an Arbitrary Waveform Generator." In 2011 IEEE 17th International Mixed-Signals, Sensors and Systems Test Workshop (IMS3TW 2011). IEEE, 2011. http://dx.doi.org/10.1109/ims3tw.2011.17.
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Shibuya, Shohei, Yutaro Kobayashi, and Haruo Kobayashi. "High-frequency low-distortion signal generation algorithm with arbitrary waveform generator." In 2015 IEEE 11th International Conference on ASIC (ASICON ). IEEE, 2015. http://dx.doi.org/10.1109/asicon.2015.7517007.
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Okawa, Hajime, Shigenori Kondo, Masaya Shigeta, Seiichiro Izawa, and Yu Fukunishi. "Generation of Velocity Fluctuations in a Boundary Layer by a Piezoelectric Actuator." In ASME-JSME-KSME 2011 Joint Fluids Engineering Conference. ASMEDC, 2011. http://dx.doi.org/10.1115/ajk2011-13018.
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A feedforward control system for suppressing the instability waves in a boundary layer has been examined and improved. An array of piezoelectric actuators attached on a flat-plate surface was used as an active control device of the feedforward control system. Previous works have demonstrated that an array of piezoelectric actuators was able to generate controlling waves that were 180 degrees out-of-phase with the target instability waves, but finding the optimum timing and amplitude for driving the actuators depended on the experience and skill of the experimenters. To resolve this problem, we focused our attention on the process of generating these artificial waves. First, the flow field near an actuator was measured in detail in order to clarify the wave-generating process. It was found that the velocity fluctuation pattern started to appear from the actuator’s surface, not from its trailing edge. Next, the effect of the driving signal waveform on the control was examined by comparing two different waveforms, sinusoidal and rectangular. A difference was found only in the third harmonic component of the generated velocity fluctuations, where the peak in the rectangular case was higher than that in the sinusoidal case. This suggested that it was not necessary to operate the actuators by a sinusoidal signal. Finally, a new semi-automatic algorithm for determining the control parameters was proposed and applied in an active feedforward control experiment. Our new algorithm demonstrated its ability to reduce the amplitude of the incoming oblique waves.
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Reineix, Gwenael, Romain Negrier, Michele Lalande, Vincent Couderc, Joel Andrieu, and Laurent Desrumaux. "Optoelectronic waveforms generation: PCSS characterization and genetic algorithm." In 2017 47th European Microwave Conference (EuMC). IEEE, 2017. http://dx.doi.org/10.23919/eumc.2017.8231108.
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Reineix, Gwenael, Romain Negrier, Michele Lalande, Vincent Couderc, Joel Andrieu, and Laurent Desrumaux. "Optoelectronic waveforms generation: PCSS characterization and genetic algorithm." In 2017 European Radar Conference (EURAD). IEEE, 2017. http://dx.doi.org/10.23919/eurad.2017.8249263.
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Linlin Zhang, Kai Xu, Fang Shi, Yunbo Wang, and Shuozheng Liu. "Single-Phase-to-Ground Fault Diagnosis Method based on Waveform Features and Association Rule Algorithm." In 8th Renewable Power Generation Conference (RPG 2019). Institution of Engineering and Technology, 2019. http://dx.doi.org/10.1049/cp.2019.0297.
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Donald, J. Adam, Erik Wielemaker, Edgar Velez, Lin Liang, Ting Lei, Matthew Blyth, and Romain Prioul. "Digital Transformation of Borehole Sonic Services in the Oil and Gas Industry." In International Petroleum Technology Conference. IPTC, 2021. http://dx.doi.org/10.2523/iptc-21205-ms.
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Abstract Sonic data are commonly acquired in exploration, appraisal, and development wells using wireline, logging-while-drilling, or through-the-bit conveyance for applications within petrophysics, geophysics, geomechanics, and geology disciplines. The measurement data require processing to obtain elastic wave slownesses (inverse of velocity) and associated attributes before the results can be used in petrotechnical workflows. The objective of the digital transformation is to streamline and automate the processing workflow to reduce user intervention and turnaround time while increasing the accuracy of results and possibly extracting more answers by fully utilizing all waveform attributes, which consequently benefits downstream applications. There are four workflows that are the foundation of the transformation. They support the overall goals of reducing user interactions and providing robust results in a timely manner for continuous slowness logs. First, data-driven inversions done during acquisition with automatic quality control and interpretation flags immediately provide assurance about the data quality and identify formation intervals that require further evaluation. Second, automatic dipole-flexural shear extraction is done using physics-based machine learning (ML) where purely data-driven models are inadequate due to borehole or geological conditions. The physics-based ML utilizes cloud-based computing that is needed for large volume synthetic data generation and neural network training. Third, a multiresolution analysis of the monopole waves for the compressional slowness uses automatic peak detection on multiple receiver levels removing any subjective manual labeling after the semblance processing. Finally, the multimode (flexural and Stoneley) inversion determines anisotropic constants and accounts for mud-speed variations in the borehole, including detailed uncertainties. The new methods address underlying concerns most users and waveform processing experts already observe in their sonic deliverables. Enabling wellsite algorithms to be more automatic and data driven improves the robustness of the field deliverables and provides insight into the quality of the data. For the shortcomings with regards to borehole or geological conditions such as laminations, sharp lithological transitions, or the presence of anisotropy, the physics-based ML is shown to honor the physics of the dipole flexural mode, while the multiresolution for the monopole provides physics-based reasoning for discrepancies between the geological layering and receiver aperture. By incorporating the range of results derived from the inversions with advanced interpretations such as transversely isotropic constants, these uncertainties can be further used in stochastic models in downstream workflows. All these methods are fully automated and can be done in a short timeframe to be used without doubt in operations.
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Lima Silva, Veronica Maria, Raimundo Carlos Silverio Freire, and Cleonilson Protasio de Souza. "Arbitrary waveform generator based on the Berlekamp-Massey Algorithm." In 2016 1st International Symposium on Instrumentation Systems, Circuits and Transducers (INSCIT). IEEE, 2016. http://dx.doi.org/10.1109/inscit.2016.7598203.
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Johnson, Preston T. "Fleet Wide Monitoring: Sensors to Prognostics." In NCSL International Workshop & Symposium. NCSL International, 2014. http://dx.doi.org/10.51843/wsproceedings.2014.52.
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Next generation fleet wide asset monitoring solutions are incorporating machine failure prediction and prognostics technologies. These technologies build on signal processing of vibration time waveforms, process parameters, and operating conditions of the machine. For prognostics algorithms to work well, the signal processing algorithms need to be applied correctly and the results need to be reliable. This paper provides a survey of signal processing techniques as applied to specific machine component with a focus on the output and use with prognostics technologies. With properly organized outputs, prognostics algorithms transform the fleet condition and health management challenge into a deployable fleet health management solution. To arrive at the deployable fleet management solution, a systematic approach in the design of the prognostics system is preferable. This approach includes data and model driven failure patterns, sensory data connectivity from deployed assets, prognostics analytical applications, and advisory generation outputs which guide the asset owners and maintainers.
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Xiao, Yindong, Guangkun Guo, Yu Chen, Wenhao Zhao, Ke Liu, and Lei Huang. "An Algorithm for Selecting Sampling Rate in Arbitrary Waveform Generator." In 2018 IEEE AUTOTESTCON. IEEE, 2018. http://dx.doi.org/10.1109/autest.2018.8532524.
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