Log in

Relevant bibliographies by topics / Signals / Journal articles

Journal articles on the topic 'Signals'

To see the other types of publications on this topic, follow the link: Signals.

Author: Grafiati

Published: 4 June 2021

Last updated: 4 March 2023

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Signals.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Koh, Kunghee, and Eun Ryoung Paik. "Analysis of Danish Haptic Signals in “Haptic signals: 139 new and known signals”." Journal of special education : theory and practice 22, no. 2 (June 30, 2021): 125–51. http://dx.doi.org/10.19049/jsped.2021.22.2.06.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Mace, Douglas, Mark Finkle, and Sara Pennak. "Daytime Photometric Requirements for Pedestrian Signals." Transportation Research Record: Journal of the Transportation Research Board 1605, no. 1 (January 1997): 41–48. http://dx.doi.org/10.3141/1605-06.

Full text

Abstract:

Forty-eight senior citizens participated in a field study of the visibility of letters and symbols in pedestrian traffic signals. Subjects were asked to identify signal messages from distances of 18.3 m and 29.3 m, with signal voltage set at 100 percent, 75 percent, and 50 percent of full power. Incandescent, fiber-optic, and light-emitting diode commercially available pedestrian signals were tested, including 22.9-cm and 30.5-cm rectangular signal housings and two round red-amber-green signals with symbol masks. Each subject was asked to identify the signal’s location in the test stimuli array, to name the signal’s display configuration (Walk, Don’t Walk, walking person, or hand), and to assess the signal’s brightness on a five-point scale. Analyses also were conducted on the percentage of responses about “too bright” signals and subject uncertainty about the signal message. Testing was conducted only on bright sunny days but did not include the worst-case condition of direct sunlight on the signal face. The analysis of recognition, uncertainty, and “too bright” responses suggested that a signal intensity of 25 cd minimizes the frequency of both “too bright” and uncertain responses regardless of size, distance, or technology, or whether the message is symbol or text. The data further suggest that 22.9-cm incandescent signals provide sufficient visibility with less phantom effect than 30.5-cm signals.

APA, Harvard, Vancouver, ISO, and other styles

3

Gudiškis, Andrius. "HEART BEAT DETECTION IN NOISY ECG SIGNALS USING STATISTICAL ANALYSIS OF THE AUTOMATICALLY DETECTED ANNOTATIONS / ŠIRDIES DŪŽIŲ NUSTATYMAS IŠ IŠKRAIPYTŲ EKG SIGNALŲ ATLIEKANT AUTOMATIŠKAI APTIKTŲ ATSKAITŲ STATISTINĘ ANALIZĘ." Mokslas – Lietuvos ateitis 7, no. 3 (July 13, 2015): 300–303. http://dx.doi.org/10.3846/mla.2015.787.

Full text

Abstract:

This paper proposes an algorithm to reduce the noise distortion influence in heartbeat annotation detection in electrocardiogram (ECG) signals. Boundary estimation module is based on energy detector. Heartbeat detection is usually performed by QRS detectors that are able to find QRS regions in a ECG signal that are a direct representation of a heartbeat. However, QRS performs as intended only in cases where ECG signals have high signal to noise ratio, when there are more noticeable signal distortion detectors accuracy decreases. Proposed algorithm uses additional data, taken from arterial blood pressure signal which was recorded in parallel to ECG signal, and uses it to support the QRS detection process in distorted signal areas. Proposed algorithm performs as well as classical QRS detectors in cases where signal to noise ratio is high, compared to the heartbeat annotations provided by experts. In signals with considerably lower signal to noise ratio proposed algorithm improved the detection accuracy to up to 6%. Širdies ritmas yra vienas svarbiausių ir daugiausia informacijos apie pacientų būklę teikiančių fiziologinių parametrų. Širdies ritmas nustatomas iš elektrokardiogramos (EKG), atliekant QRS regionų, kurie yra interpretuojami kaip širdies dūžio ãtskaitos, paiešką. QRS regionų aptikimas yra klasikinis uždavinys, nagrinėjamas jau keletą dešimtmečių, todėl širdies dūžių nustatymo iš EKG signalų metodų yra labai daug. Deja, šie metodai tikslūs ir patikimi tik esant dideliam signalo ir triukšmo santykiui. Kai EKG signalai labai iškraipomi, QRS aptiktuvai ne visada gali atskirti QRS regioną, o kartais jį randa ten, kur iš tikro jo būti neturėtų. Straipsnyje siūlomas algoritmas, kurį taikant sumažinama triukšmo įtaka nustatant iš EKG signalų QRS regionus. Tam naudojamas QRS aptiktuvas, kartu prognozuojantis širdies dūžio atskaitą. Remiamasi arterinio kraujo spaudimo signalo duomenimis, renkama atskaitų statistika ir atliekama jos analizė.

APA, Harvard, Vancouver, ISO, and other styles

4

Davis, Daniel J., and John H. Challis. "Vertical Ground Reaction Force Estimation From Benchmark Nonstationary Kinematic Data." Journal of Applied Biomechanics 37, no. 3 (June 1, 2021): 272–76. http://dx.doi.org/10.1123/jab.2020-0237.

Full text

Abstract:

Time-differentiating kinematic signals from optical motion capture amplifies the inherent noise content of those signals. Commonly, biomechanists address this problem by applying a Butterworth filter with the same cutoff frequency to all noisy displacement signals prior to differentiation. Nonstationary signals, those with time-varying frequency content, are widespread in biomechanics (eg, those containing an impact) and may necessitate a different filtering approach. A recently introduced signal filtering approach wherein signals are divided into sections based on their energy content and then Butterworth filtered with section-specific cutoff frequencies improved second derivative estimates in a nonstationary kinematic signal. Utilizing this signal-section filtering approach for estimating running vertical ground reaction forces saw more of the signal’s high-frequency content surrounding heel strike maintained without allowing inappropriate amounts of noise contamination in the remainder of the signal. Thus, this signal-section filtering approach resulted in superior estimates of vertical ground reaction forces compared with approaches that either used the same filter cutoff frequency across the entirety of each signal or across the entirety of all signals. Filtering kinematic signals using this signal-section filtering approach is useful in processing data from tasks containing an impact when accurate signal second derivative estimation is of interest.

APA, Harvard, Vancouver, ISO, and other styles

5

Nie, Chun Yan, Rui Li, and Ju Wang. "Emotion Recognition Based on Chaos Characteristics of Physiological Signals." Applied Mechanics and Materials 380-384 (August 2013): 3750–53. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.3750.

Full text

Abstract:

Changes of physiological signals are affected by human emotions, but also the emotional fluctuations are reflected by the body's variation of physiological signal's feature. Physiological signal is a non-linear signal ,nonlinear dynamics and biomedical engineering ,which based on chaos theory, providing us a new method for studying on the parameters of these complex physiological signals which can hardly described by the classical theory. This paper shows physiological emotion signal recognition system based on the chaotic characteristics, and than describes some current applications of chaotic characteristics for multiple physiological signals on emotional recognition.

APA, Harvard, Vancouver, ISO, and other styles

6

Shellenberger, Richard O., and Paul Lewis. "Signal Control by Six Signals." Psychological Reports 63, no. 1 (August 1988): 311–18. http://dx.doi.org/10.2466/pr0.1988.63.1.311.

Full text

Abstract:

In previous signal-control experiments, several types of stimuli elicited pecking when paired with peck-contingent grain. Here, we compared the effectiveness of an auditory stimulus and five visual stimuli. For 12 pigeons, the first keypeck to follow the offset of a 4-sec. signal was reinforced with grain. We examined the following signals: a tone, a white keylight, a dark keylight, a keylight that changed from white to red, houselight onset, and houselight offset. All signals acquired strong control over responding. According to one measure, percent of signals with a peck, houselight offset showed less control than the others; according to another measure, pecking rate, the white keylight showed greater control than the others. In this experiment, we found that a wide variety of stimuli can elicit strong pecking in the signal-control procedure. The present findings increase the chances that in past conditioning experiments, some keypecks thought to be due to contingencies of reinforcement were in fact elicited.

APA, Harvard, Vancouver, ISO, and other styles

7

Yin, Zhi Gang. "The Research of the Spectral Features of Vibration Signals from Underground Railway Based on Wavelet Transform." Advanced Materials Research 243-249 (May 2011): 3463–67. http://dx.doi.org/10.4028/www.scientific.net/amr.243-249.3463.

Full text

Abstract:

Using wavelet transform, signal’s frequency properties of vibration induced by underground are analyzed A MATLAB program is developed in order to decompose and reconstruct acceleration signals. The law that acceleration signals change in time-spectral domain is got. Then the relations of vibration signal’s maximum acceleration, energy, frequency and spectral are discussed. In contrast to conventional Fourier Transform， wavelet analysis can provide the evolution of spectral features of a signal as this evolves in time. It is ideal for random and non-stationary signal analysis.

APA, Harvard, Vancouver, ISO, and other styles

8

Lan, Xiang, Min Zhang, and Jin-Xing Li. "OFDM Chirp Waveform Design Based on Subchirp Bandwidth Overlap and Segmented Transmitting for Low Correlation Interference in MIMO Radar." Sensors 19, no. 12 (June 14, 2019): 2696. http://dx.doi.org/10.3390/s19122696.

Full text

Abstract:

There are some special merits for the orthogonal frequency division multiplexing (OFDM) chirp waveform as multiple input multiple output (MIMO) signals. This signal has high range resolution, good Doppler tolerance, and constant modulus superiority since it exploits a full bandwidth and is based on chirp signals. The correlation sidelobe peaks level are critical for the detection requirement of MIMO radar signals, however conventional OFDM chirp signals produce high autocorrelation sidelobe peaks (ASP) and cross-correlation peaks (CP), which reduces detection performance. In this paper, we explore the structure of OFDM chirp signals’ autocorrelation function and proposed a scheme to reduce the designed signal’s ASP by a designing suitable range of subchirp bandwidth and a segmented transmit-receive mode. Next, we explore a suitable range of interval between the chirp rates of each two signals to reduce the CP. The simulation of designed signals verifies the effectiveness of the proposed methods in the reduction of ASP and CP, with the correlation performance being compared with recent relate studies. In addition, the multiple signals detection and one-dimensional range image simulation show the good detection performance of a designed signal in MIMO radar detection.

APA, Harvard, Vancouver, ISO, and other styles

9

Oo, Thandar, and Pornchai Phukpattaranont. "Signal-to-Noise Ratio Estimation in Electromyography Signals Contaminated with Electrocardiography Signals." Fluctuation and Noise Letters 19, no. 03 (February 17, 2020): 2050027. http://dx.doi.org/10.1142/s0219477520500273.

Full text

Abstract:

When electromyography (EMG) signals are collected from muscles in the torso, they can be perturbed by the electrocardiography (ECG) signals from heart activity. In this paper, we present a novel signal-to-noise ratio (SNR) estimate for an EMG signal contaminated by an ECG signal. We use six features that are popular in assessing EMG signals, namely skewness, kurtosis, mean average value, waveform length, zero crossing and mean frequency. The features were calculated from the raw EMG signals and the detail coefficients of the discrete stationary wavelet transform. Then, these features are used as inputs to a neural network that outputs the estimate of SNR. While we used simulated EMG signals artificially contaminated with simulated ECG signals as the training data, the testing was done with simulated EMG signals artificially contaminated with real ECG signals. The results showed that the waveform length determined with raw EMG signals was the best feature for estimating SNR. It gave the highest average correlation coefficient of 0.9663. These results suggest that the waveform length could be deployed not only in EMG recognition systems but also in EMG signal quality measurements when the EMG signals are contaminated by ECG interference.

APA, Harvard, Vancouver, ISO, and other styles

10

Cheng, Xiu Zhi, Zhen Yu, and Guang Zhu. "Experimental Study of Mine AE Signal Based on Wavelet Analysis." Applied Mechanics and Materials 148-149 (December 2011): 1127–30. http://dx.doi.org/10.4028/www.scientific.net/amm.148-149.1127.

Full text

Abstract:

Because the wavelet transform can characterize the local signals in time and frequency domain, in the coal mine’s sound signals’ process, an audio signal processing based on wavelet analysis is proposed, the audio signal P wave is isolated and determined by wavelet transform, at the same time, the earthquake source can be located. Through the research of the mine AE signal’s activity patterns, the sound monitoring technology to forecast the mine power disaster is achieved.

APA, Harvard, Vancouver, ISO, and other styles

11

Shelishiyah, R., M. Bharani Dharan, T. Kishore Kumar, R. Musaraf, and Thiyam Deepa Beeta. "Signal Processing for Hybrid BCI Signals." Journal of Physics: Conference Series 2318, no. 1 (August 1, 2022): 012007. http://dx.doi.org/10.1088/1742-6596/2318/1/012007.

Full text

Abstract:

Abstract The brain signals can be converted to a command to control some external device using a brain-computer interface system. The unimodal BCI system has limitations like the compensation of the accuracy with the increase in the number of classes. In addition to this many of the acquisition systems are not robust for real-time application because of poor spatial or temporal resolution. To overcome this, a hybrid BCI technology that combines two acquisition systems has been introduced. In this work, we have discussed a preprocessing pipeline for enhancing brain signals acquired from fNIRS (functional Near Infrared Spectroscopy) and EEG (Electroencephalography). The data consists of brain signals for four tasks – Right/Left hand gripping and Right/Left arm raising. The EEG (brain activity) data were filtered using a bandpass filter to obtain the activity of mu (7-13 Hz) and beta (13-30 Hz) rhythm. The Oxy-haemoglobin and Deoxy-haemoglobin (HbO and HbR) concentration of the fNIRS signal was obtained with Modified Beer Lambert Law (MBLL). Both signals were filtered using a fifth-order Butterworth band pass filter and the performance of the filter is compared theoretically with the estimated signal-to-noise ratio. These results can be used further to improve feature extraction and classification accuracy of the signal.

APA, Harvard, Vancouver, ISO, and other styles

12

Minasian, R. A. "Photonic signal processing of microwave signals." IEEE Transactions on Microwave Theory and Techniques 54, no. 2 (February 2006): 832–46. http://dx.doi.org/10.1109/tmtt.2005.863060.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Milligan, Graeme. "All the right signals Signal transduction." Trends in Biochemical Sciences 22, no. 10 (October 1997): 410. http://dx.doi.org/10.1016/s0968-0004(97)82532-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Lessard, Charles S. "Signal Processing of Random Physiological Signals." Synthesis Lectures on Biomedical Engineering 1, no. 1 (January 2006): 1–232. http://dx.doi.org/10.2200/s00012ed1v01y200602bme001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Birdsall, Theodore G., Kurt Metzger, and Matthew A. Dzieciuch. "Signals, signal processing, and general results." Journal of the Acoustical Society of America 96, no. 4 (October 1994): 2343–52. http://dx.doi.org/10.1121/1.410106.

Full text

APA, Harvard, Vancouver, ISO, and other styles

16

Duan, Li, Jianxian Cai, Juan Liang, Danqi Chen, and Xiaoye Sun. "Identification and Analysis of Non-Stationary Time Series Signals Based on Data Preprocessing and Deep Learning." Traitement du Signal 39, no. 5 (November 30, 2022): 1703–9. http://dx.doi.org/10.18280/ts.390528.

Full text

Abstract:

Deep learning is not the most accurate way for recognizing time series signals, and it is unable to identify non-stationary time series signals with numerous chaotic classes. Moreover, the signal detection benefits from data preprocessing have gone unnoticed. Therefore, this paper investigates the detection and analysis of non-stationary time series signals using deep learning and data preprocessing. The fitting model of the historical stationarity index is built based on the Gaussian mixture model of single Gaussian models, and the change point of the non-stationary time series signal is detected. To further increase the signal's recognition rate, the non-stationary time series signal is preprocessed using the truncated migration algorithm. The main classification task and the auxiliary classification tasks are constructed to identify non-stationary time series signals characterized by huge chaotic classes through multi-task learning. The efficiency of the suggested method and model is validated by experimental data.

APA, Harvard, Vancouver, ISO, and other styles

17

Filonenko, Sergay, Viacheslav Stadnychenko, and Anzhelika Stakhova. "MODELLING OF ACOUSTIC EMISSION SIGNALS AT FRICTION OF MATERIALS’ SURFACE LAYERS/MEDŽIAGŲ PAVIRŠIAUS TRINTIES AKUSTINĖS EMISIJOS SIGNALŲ MODELIAVIMAS." Aviation 12, no. 3 (September 30, 2008): 87–94. http://dx.doi.org/10.3846/1648-7788.2008.12.87-94.

Full text

Abstract:

A model of the signal of acoustic emission resulting from the normal wear of friction pairs is considered. Its mathematical description is obtained. Modelling of acoustic emission signals at varying strained/deformed state and rotation speed of initial friction pairs is done. The basic regularities of the transformation of acoustic emission form and those of its (emission) parameters of resulting signals are determined. Experimental research of acoustic emission signals is performed and proved to be good when compared to the results of theoretical research. Santrauka Išnagrinėtas akustinės emisijos signalų, kurie susidaro normaliame besitrinančių porų dilime, modelis ir jis matematiškai aprašytas. Atliktas akustinės emisijos signalų modeliavimas esant įvairiam pradinių trinties porų sukimosi greičiui ir įtempimų/deformacijų būsenai. Nustatyti pagrindiniai akustinės emisijos signalų formos ir parametrų transformacijos dėsningumai. Atliktas eksperimentinis akustinės emisijos signalų tyrimas, kurio rezultatai gerai sutapo su teoriniais.

APA, Harvard, Vancouver, ISO, and other styles

18

Fan, Di, Mao Yong Cao, and Lax Misha Rai. "A Novel Method of Identifying Threshold for Gabor Transform Filter Based on Inter-Cluster Distance Probability." Key Engineering Materials 467-469 (February 2011): 1985–90. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.1985.

Full text

Abstract:

Gabor transform suitable for time-frequency analysis and good for filtering non-stationary signals. The threshold of the Gabor transform filter is a key factor for the filter’s effectiveness. The popularly used threshold obtained by linear method is not suitable for non-stationary signals with low signal to noise ratio (SNR) because, it cannot separate the expansion coefficients of noise and useful signals. In this paper, a novel method to identify Gabor transform filter’s threshold based on initial highest inter-cluster distance probability is proposed. Simulation experiments have been carried out under several conditions. The experimental results show that the proposed threshold is highly suitable, especially when the signal’s SNR is very low and the filter output is very consistent to the real original signal and keeps no pseudo signal in zero regions.

APA, Harvard, Vancouver, ISO, and other styles

19

Zhao, Lin. "Numerical Control Lathe Cutting Force Signal On-Line Monitoring Design." Applied Mechanics and Materials 711 (December 2014): 329–32. http://dx.doi.org/10.4028/www.scientific.net/amm.711.329.

Full text

Abstract:

The main research direction of Numerical control lathe cutting force signal on-line monitoring is to process real-time monitoring, using the sensor, charge amplifier, video acquisition card and computer to collect data and signal. Signal acquisition makes use of the piezoelectric sensor signals and send them to the computer in order to acquire the real-time data and display the dynamic signal so that monitor the process. Signal processing is the course that data will be collected for subsequent processing and analyzing. It includes display, filtering, correlation analysis, spectral analysis, etc. We can conclude the signal’s characteristics after the time domain and frequency domain analysis of signals.

APA, Harvard, Vancouver, ISO, and other styles

20

Campbell, Cheryl R., and Susan T. Jackson. "Transparency of One-Handed Amer-Ind Hand Signals to Nonfamiliar Viewers." Journal of Speech, Language, and Hearing Research 38, no. 6 (December 1995): 1284–89. http://dx.doi.org/10.1044/jshr.3806.1284.

Full text

Abstract:

Thirty non-brain-damaged adults viewed 104 videotaped Amer-Ind hand signals. The majority of these hand signals were produced with one hand; 60 originally one-handed gestures and 31 left-hand adaptations of two-handed gestures were included in the data analyses. Nineteen subjects were between the ages of 20 and 30 years (younger group), and 11 subjects were between the ages of 50 and 69 years (older group). After viewing each hand signal twice in succession, the subjects wrote at least one word for that signal’s meaning. The mean percentage of one-handed signals correctly identified was 48.2%; these signals varied widely in transparency (0% to 100%). The left-hand adaptations were significantly lower in transparency than the originally one-handed signals. The younger and older subjects did not differ in the mean percentage of one-handed signals they identified correctly (49.0% and 46.4%, respectively). However, some individual hand signals were easier for the younger subjects to identify; the opposite was also true.

APA, Harvard, Vancouver, ISO, and other styles

21

Elghamrawy, Haidy, Malek Karaim, Mohamed Tamazin, and Aboelmaged Noureldin. "Experimental Evaluation of the Impact of Different Types of Jamming Signals on Commercial GNSS Receivers." Applied Sciences 10, no. 12 (June 20, 2020): 4240. http://dx.doi.org/10.3390/app10124240.

Full text

Abstract:

The received global navigation satellite system (GNSS) signal has a very low power due to traveling a very long distance and to the nature of the signal’s propagation medium. Thus, GNSS signals are easily susceptible to signal interference. Signal interference can cause severe degradation or interruption in GNSS position, navigation, and timing (PNT) services which could be very critical, especially in safety-critical applications. The objective of this paper is to evaluate the impact of the presence of jamming signals on a high-end GNSS receiver and investigate the benefits of using a multi-constellation system under such circumstances. Several jamming signals are considered in this research, including narrowband and wideband signals that are located on GPS L1 or GLONASS L1 frequency bands. Quasi-real dynamic trajectories are generated using the Spirent™ GSS6700 GNSS signal simulator combined with an interference signal generator through a Spirent™ GSS8366 unit. The performance evaluation was carried out using several evaluation metrics, including signal power degradation, navigation solution availability, dilution of precision (DOP), and positioning accuracy. The multi-constellation system presented better performance over the global positioning system (GPS)-only constellation in most cases. Moreover, jamming the GPS band caused more critical effects than jamming the GLONASS band.

APA, Harvard, Vancouver, ISO, and other styles

22

Xia, Xiang-Gen. "On BT-limited Signals." WSEAS TRANSACTIONS ON SIGNAL PROCESSING 19 (February 24, 2023): 13–18. http://dx.doi.org/10.37394/232014.2023.19.2.

Full text

Abstract:

In this paper, we introduce and characterize a subspace of bandlimited signals. The subspace consists of all bandlimited signals such that the non-zero parts of their Fourier transforms are pieces of some T bandlimited signals. The signals in the subspace are called BT-limited signals and the subspace is named as BT-limited signal space. For BT-limited signals, a signal extrapolation with an analytic error estimate exists outside the interval [−T, T ] of given signal values with errors. Some new properties about and applying BT-limited signals are also presented.

APA, Harvard, Vancouver, ISO, and other styles

23

Sriyanto, Sesar Prabu Dwi. "Adaptive seismic noise reduction using Wiener filter." Jurnal Teknologi dan Sistem Komputer 8, no. 1 (October 17, 2019): 12–20. http://dx.doi.org/10.14710/jtsiskom.8.1.2020.12-20.

Full text

Abstract:

Seismic noise disrupts the earthquake observation system due to the frequency and amplitude of seismic noise similar to the earthquake signal. The filter process is one of the methods that can be used to reduce seismic noise. In this study, the Wiener filter algorithm was designed with the Decision-Directed method for Apriori SNR estimation. This filter was chosen because it is adaptive, so it can adjust to environmental conditions without requiring manual parameter settings. The data used are earthquake signals that occur in the Palu area, Central Sulawesi, which are recorded on PKA29 temporary seismic station from February 3 to April 28, 2015. After each signal data has been filtered, then it is evaluated by calculating SNR differences before and after filtering, the signal's dominant frequency, and the cross-correlation of the signal before and after filtering. As a result, the Wiener filter is able to reduce the noise content in earthquake signals according to noisy frequencies before earthquake signals. The impact is that SNR has increased with an average of 8.056 dB. In addition, this filter is also able to maintain the shape of earthquake signals. This is indicated by the normalization value of the cross-correlation between signals before and after the filter which ranges from 0.703 to 1.00.

APA, Harvard, Vancouver, ISO, and other styles

24

Yung, S. K., and D. W. Clarke. "Local Sensor Validation." Measurement and Control 22, no. 5 (June 1989): 132–41. http://dx.doi.org/10.1177/002029408902200502.

Full text

Abstract:

Current approaches to plant fault detection require an overall process model. This paper argues that a hierarchical scheme is more efficient in which the lowest level concentrates on validating the signals transmitted by individual sensors. Signals are described in terms of standard time-series models. A fault is defined by the signal's deviation from its expected behaviour and various signal processing techniques are described which detect these aberrations.

APA, Harvard, Vancouver, ISO, and other styles

25

Bateneva, T. V., N. S. Budvis, and N. P. Khmyrova. "SIGNAL-CODE CONSTRUCTIONS USING FREQUENCY-TIME SIGNALS." RADIO COMMUNICATION TECHNOLOGY, no. 38 (2018): 9–21. http://dx.doi.org/10.33286/2075-8693-2018-38-9-21.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Mingjiang Shi, Xiaoyan Zhuang, and He Zhang. "Signal Reconstruction for Frequency Sparse Sampling Signals." Journal of Convergence Information Technology 8, no. 9 (May 15, 2013): 1197–203. http://dx.doi.org/10.4156/jcit.vol8.issue9.147.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Elgendi, Mohamed. "Optimal Signal Quality Index for Photoplethysmogram Signals." Bioengineering 3, no. 4 (September 22, 2016): 21. http://dx.doi.org/10.3390/bioengineering3040021.

Full text

APA, Harvard, Vancouver, ISO, and other styles

28

Venkatachalam, K. L., Joel E. Herbrandson, and Samuel J. Asirvatham. "Signals and Signal Processing for the Electrophysiologist." Circulation: Arrhythmia and Electrophysiology 4, no. 6 (December 2011): 965–73. http://dx.doi.org/10.1161/circep.111.964304.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Venkatachalam, K. L., Joel E. Herbrandson, and Samuel J. Asirvatham. "Signals and Signal Processing for the Electrophysiologist." Circulation: Arrhythmia and Electrophysiology 4, no. 6 (December 2011): 974–81. http://dx.doi.org/10.1161/circep.111.964973.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Frey, Douglas R. "Signal conditioning circuit for compressing audio signals." Journal of the Acoustical Society of America 103, no. 1 (January 1998): 17. http://dx.doi.org/10.1121/1.423132.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Lu, Jie, Naveen Verma, and Niraj K. Jha. "Compressed Signal Processing on Nyquist-Sampled Signals." IEEE Transactions on Computers 65, no. 11 (November 1, 2016): 3293–303. http://dx.doi.org/10.1109/tc.2016.2532861.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Ask, Per. "Ultrasound imaging. Waves, signals and signal processing." Ultrasound in Medicine & Biology 28, no. 3 (March 2002): 401–2. http://dx.doi.org/10.1016/s0301-5629(01)00520-8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Hoch, James A., and K. I. Varughese. "Keeping Signals Straight in Phosphorelay Signal Transduction." Journal of Bacteriology 183, no. 17 (September 1, 2001): 4941–49. http://dx.doi.org/10.1128/jb.183.17.4941-4949.2001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Kuiper, D. "Signals and signal transduction pathways in plants." Scientia Horticulturae 68, no. 1-4 (March 1997): 258–59. http://dx.doi.org/10.1016/s0304-4238(96)00969-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Vosvrda, Miloslav S. "Discrete random signals and statistical signal processing." Automatica 29, no. 6 (November 1993): 1617. http://dx.doi.org/10.1016/0005-1098(93)90033-p.

Full text

APA, Harvard, Vancouver, ISO, and other styles

36

Kale, Uma, and Edward Voigtman. "Signal processing of transient atomic absorption signals." Spectrochimica Acta Part B: Atomic Spectroscopy 50, no. 12 (October 1995): 1531–41. http://dx.doi.org/10.1016/0584-8547(95)01380-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

37

Munni, Pattan. "Simulation of Signals with Field Signal Simulator." IOSR Journal of Electronics and Communication Engineering 7, no. 3 (2013): 07–12. http://dx.doi.org/10.9790/2834-0730712.

Full text

APA, Harvard, Vancouver, ISO, and other styles

38

Pagot, Jean-Baptiste, Olivier Julien, Paul Thevenon, Francisco A. Fernandez, and Margaux Cabantous. "Signal Quality Monitoring for New GNSS Signals." Navigation 65, no. 1 (March 2018): 83–97. http://dx.doi.org/10.1002/navi.218.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Kawamoto, Mitsuru, A. K. Barros, A. Mansour, Kiyotoshi Matsuoka, and Noboru Ohnishi. "Blind signal separation for convolved nonstationary signals." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 84, no. 2 (2000): 21–29. http://dx.doi.org/10.1002/1520-6440(200102)84:2<21::aid-ecjc3>3.0.co;2-p.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Becker, Florent, Tom Besson, Jérôme Durand-Lose, Aurélien Emmanuel, Mohammad-Hadi Foroughmand-Araabi, Sama Goliaei, and Shahrzad Heydarshahi. "Abstract Geometrical Computation 10." ACM Transactions on Computation Theory 13, no. 1 (March 2021): 1–31. http://dx.doi.org/10.1145/3442359.

Full text

Abstract:

Signal machines form an abstract and idealized model of collision computing. Based on dimensionless signals moving on the real line, they model particle/signal dynamics in Cellular Automata. Each particle, or signal , moves at constant speed in continuous time and space. When signals meet, they get replaced by other signals. A signal machine defines the types of available signals, their speeds, and the rules for replacement in collision. A signal machine A simulates another one B if all the space-time diagrams of B can be generated from space-time diagrams of A by removing some signals and renaming other signals according to local information. Given any finite set of speeds S we construct a signal machine that is able to simulate any signal machine whose speeds belong to S . Each signal is simulated by a macro-signal , a ray of parallel signals. Each macro-signal has a main signal located exactly where the simulated signal would be, as well as auxiliary signals that encode its id and the collision rules of the simulated machine. The simulation of a collision, a macro-collision , consists of two phases. In the first phase, macro-signals are shrunk, and then the macro-signals involved in the collision are identified and it is ensured that no other macro-signal comes too close. If some do, the process is aborted and the macro-signals are shrunk, so that the correct macro-collision will eventually be restarted and successfully initiated. Otherwise, the second phase starts: the appropriate collision rule is found and new macro-signals are generated accordingly. Considering all finite sets of speeds S and their corresponding simulators provides an intrinsically universal family of signal machines.

APA, Harvard, Vancouver, ISO, and other styles

41

Fuss, Franz Konstantin. "A Robust Algorithm for Optimisation and Customisation of Fractal Dimensions of Time Series Modified by Nonlinearly Scaling Their Time Derivatives: Mathematical Theory and Practical Applications." Computational and Mathematical Methods in Medicine 2013 (2013): 1–19. http://dx.doi.org/10.1155/2013/178476.

Full text

Abstract:

Standard methods for computing the fractal dimensions of time series are usually tested with continuous nowhere differentiable functions, but not benchmarked with actual signals. Therefore they can produce opposite results in extreme signals. These methods also use different scaling methods, that is, different amplitude multipliers, which makes it difficult to compare fractal dimensions obtained from different methods. The purpose of this research was to develop an optimisation method that computes the fractal dimension of a normalised (dimensionless) and modified time series signal with a robust algorithm and a running average method, and that maximises the difference between two fractal dimensions, for example, a minimum and a maximum one. The signal is modified by transforming its amplitude by a multiplier, which has a non-linear effect on the signal’s time derivative. The optimisation method identifies the optimal multiplier of the normalised amplitude for targeted decision making based on fractal dimensions. The optimisation method provides an additional filter effect and makes the fractal dimensions less noisy. The method is exemplified by, and explained with, different signals, such as human movement, EEG, and acoustic signals.

APA, Harvard, Vancouver, ISO, and other styles

42

Treetrong, Juggrapong. "Application of Signal Processing for Motor Condition Monitoring Based on Filtered-Signals and Eliminated-Signals." Advanced Materials Research 378-379 (October 2011): 557–60. http://dx.doi.org/10.4028/www.scientific.net/amr.378-379.557.

Full text

Abstract:

This paper proposes new procedures of motor fault detection. The proposed methods are based on filtered-signals and eliminated-signals. Generally, the raw stator phase currents collected from the motors are firstly filtered in order to get rid of measurement noises. If the new signals are called “Filtered-Signals” and the signals eliminated from the raw stator phase currents are called “Eliminated-Signals”. The first proposed procedure is to detect the motor faults by spectrum of PSD slope from the filtered-signals. The second proposed procedure is to detect the motor faults by spectrum of the eliminated-signals. The both methods are tested on 3 different motor conditions: healthy, stator fault, and rotor fault motor at full load condition. The experiments show that the both methods can differentiate conditions clearly and they also can indicate the levels of fault severity. Thus, it can be effective when the both methods are applied simultaneously to analyze the faults

APA, Harvard, Vancouver, ISO, and other styles

43

I. S. Amiri, I. S. Amiri, and J. Ali J. Ali. "Data signal processing via manchester coding-decoding method using chaotic signals generated by PANDA ring resonator." Chinese Optics Letters 11, no. 4 (2013): 041901–41904. http://dx.doi.org/10.3788/col201311.041901.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Kertzer, Joshua D., Brian C. Rathbun, and Nina Srinivasan Rathbun. "The Price of Peace: Motivated Reasoning and Costly Signaling in International Relations." International Organization 74, no. 1 (November 5, 2019): 95–118. http://dx.doi.org/10.1017/s0020818319000328.

Full text

Abstract:

AbstractCanonical models of costly signaling in international relations (IR) tend to assume costly signals speak for themselves: a signal's costliness is typically understood to be a function of the signal, not the perceptions of the recipient. Integrating the study of signaling in IR with research on motivated skepticism and asymmetric updating from political psychology, we show that individuals’ tendencies to embrace information consistent with their overarching belief systems (and dismiss information inconsistent with it) has important implications for how signals are interpreted. We test our theory in the context of the 2015 Joint Comprehensive Plan of Action (JCPOA) on Iran, combining two survey experiments fielded on members of the American mass public. We find patterns consistent with motivated skepticism: the individuals most likely to update their beliefs are those who need reassurance the least, such that costly signals cause polarization rather than convergence. Successful signaling therefore requires knowing something about the orientations of the signal's recipient.

APA, Harvard, Vancouver, ISO, and other styles

45

Wang, Yuan Gan. "Ring-Space Array Torque Measure System and Signal Singularity Detection." Advanced Materials Research 629 (December 2012): 741–46. http://dx.doi.org/10.4028/www.scientific.net/amr.629.741.

Full text

Abstract:

Torque is the most important dynamic characteristics of the mechanically-driven system. In order to monitor the mechanical principal axis in real time, a new non-contact torque measurement system based on ring-space array sensor is proposed. This system can be used for the analysis of dynamic characteristics of the mechanical system’s axis under various loads and hard working environments. Singularity in the collected signals is most important with the mechanical system. Because of much noise was contained in collected signals, which always interferes the signal’s singularity detection. According to the different behaves of signal and noise under wavelet transform, a method with wavelet filtering and singularity detection combined is proposed. This method could realize two-dimension filtering reconstruction in both time and frequency domain, in which the singularity information in signal can be kept well while the noise will be filtered. The proposed method is suitable for singularity detection of signals under serious noise.

APA, Harvard, Vancouver, ISO, and other styles

46

Xing, Jin, Baoguo Yu, Dongkai Yang, Jie Li, Zhejia Shi, Guodong Zhang, and Feng Wang. "A Real-Time GNSS-R System for Monitoring Sea Surface Wind Speed and Significant Wave Height." Sensors 22, no. 10 (May 17, 2022): 3795. http://dx.doi.org/10.3390/s22103795.

Full text

Abstract:

This paper presents a monitoring system based on Global Navigation Satellite System (GNSS) reflected signals to provide real-time observations of sea conditions. Instead of a computer, the system uses a custom-built hardware platform that incorporates Radio Frequency (RF), Field Programmable Gate Array (FPGA), Digital Signal Processing (DSP), and Raspberry Pi for real-time signal processing. The suggested structure completes the navigation signal’s positioning as well as the reflected signal’s feature extraction. Field tests are conducted to confirm the effectiveness of the system and the retrieval algorithm described in this research. The entire system collects and analyzes signals at a coastal site in the field experiment, producing sea surface wind speed and significant wave height (SWH) that are compared to local weather station data, demonstrating the system’s practicality. The system can allow the centralized monitoring of many sites, as well as field experiments and real-time early warning at sea.

APA, Harvard, Vancouver, ISO, and other styles

47

Gelenbe, Erol. "Random Neural Networks with Negative and Positive Signals and Product Form Solution." Neural Computation 1, no. 4 (December 1989): 502–10. http://dx.doi.org/10.1162/neco.1989.1.4.502.

Full text

Abstract:

We introduce a new class of random “neural” networks in which signals are either negative or positive. A positive signal arriving at a neuron increases its total signal count or potential by one; a negative signal reduces it by one if the potential is positive, and has no effect if it is zero. When its potential is positive, a neuron “fires,” sending positive or negative signals at random intervals to neurons or to the outside. Positive signals represent excitatory signals and negative signals represent inhibition. We show that this model, with exponential signal emission intervals, Poisson external signal arrivals, and Markovian signal movements between neurons, has a product form leading to simple analytical expressions for the system state.

APA, Harvard, Vancouver, ISO, and other styles

48

Hahn, S. L., and K. M. Snopek. "Quasi-analytic multidimensional signals." Bulletin of the Polish Academy of Sciences: Technical Sciences 61, no. 4 (December 1, 2013): 1017–24. http://dx.doi.org/10.2478/bpasts-2013-0109.

Full text

Abstract:

Abstract In a recent paper, the authors have presented the unified theory of n-dimensional (n-D) complex and hypercomplex analytic signals with single-orthant spectra. This paper describes a specific form of these signals called quasi-analytic. A quasi-analytic signal is a product of a n-D low-pass (base-band) real (in general non-separable) signal and a n-D complex or hypercomplex carrier. By a suitable choice of the carrier frequency, the spectrum of a low-pass signal is shifted into a single orthant of the Fourier frequency space with a negligible leakage into other orthants. A measure of this leakage is defined. Properties of quasi-analytic signals are studied. Problems of polar representation of quasi-analytic signals and of its lower rank representation are discussed.

APA, Harvard, Vancouver, ISO, and other styles

49

BARRABÈS, C., and P. A. HOGAN. "IMPULSIVE LIGHT-LIKE SIGNALS." International Journal of Modern Physics A 17, no. 20 (August 10, 2002): 2746. http://dx.doi.org/10.1142/s0217751x02011734.

Full text

Abstract:

A general characterisation of an impulsive light–like signal was given1,2. The signal may consist of a shell of null matter and/or an impulsive gravitational wave. Both parts of the signal can be unambiguously identified3,4. The signals can be used to model bursts of gravitational radiation and light– like matter accompanying cataclysmic events such as supernovae and neutron star collisions. Also in high speed collisions of compact objects such as black–holes or neutron stars the gravitational fields of these objects resemble those of impulsive light–like signals when the objects are boosted to the speed of light. Several examples of impulsive light–like signals were presented, in particular those produced by recoil effects5 and by the Aichelburg–Sexl boost of an isolated gravitating multipole source6. The detection of these signals was also discussed7.

APA, Harvard, Vancouver, ISO, and other styles

50

Saeed, Amer T., Zaid Raad Saber, Ahmed M. Sana, and Musa A. Hameed. "Eliminating unwanted signals in sound by using digital signal processing system." Indonesian Journal of Electrical Engineering and Computer Science 18, no. 2 (May 1, 2020): 829. http://dx.doi.org/10.11591/ijeecs.v18.i2.pp829-834.

Full text

Abstract:

<p><a name="_Hlk536186602"></a><span style="font-size: 9pt; font-family: 'Times New Roman', serif;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal. </span><span style="font-family: 'Times New Roman', serif; font-size: 9pt;">Unwanted signals or noise signals in sound files are considered one of the major challenges and issues for a thousand users. It is impossible to reduce or remove these noise signals without identifying their types and ranges. Therefore, to address one of the big problems in the digital or analogue communication, which is noise signals or unwanted signals, an adaptive selection method and noise signal removal algorithm are proposed in this research. The proposed algorithm is done through specifying the types of undesirable signals, frequency, and time range, then utilizing digital signal processing system which includes design several types of digital filters based on the types and numbers of unwanted signals. Four digital filters are used in this research to remove noise signals from the sound file by implementing the proposed algorithm using Matlab Code. Results show that our proposed algorithm was done successfully and the whole noise signals were removed without any negative consequence in the output sound signal.</span></p>

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!