Relevant bibliographies by topics / Signals

Academic literature on the topic 'Signals'

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Published: 4 June 2021
Last updated: 4 March 2023

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Journal articles on the topic "Signals"

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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.

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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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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.

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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.
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Dissertations / Theses on the topic "Signals"

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Li, Jian. "Array signal processing for polarized signals and signals with known waveforms /." The Ohio State University, 1991. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487687485808063.

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Saruwatari, Hiroshi. "BLIND SIGNAL SEPARATION OF AUDIO SIGNALS." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2006. http://hdl.handle.net/2237/10406.

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Ghaderi, Foad. "Signal processing techniques for extracting signals with periodic structure : applications to biomedical signals." Thesis, Cardiff University, 2010. http://orca.cf.ac.uk/55183/.

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In this dissertation some advanced methods for extracting sources from single and multichannel data are developed and utilized in biomedical applications. It is assumed that the sources of interest have periodic structure and therefore, the periodicity is exploited in various forms. The proposed methods can even be used for the cases where the signals have hidden periodicities, i.e., the periodic behaviour is not detectable from their time representation or even Fourier transform of the signal. For the case of single channel recordings a method based on singular spectrum anal ysis (SSA) of the signal is proposed. The proposed method is utilized in localizing heart sounds in respiratory signals, which is an essential pre-processing step in most of the heart sound cancellation methods. Artificially mixed and real respiratory signals are used for evaluating the method. It is shown that the performance of the proposed method is superior to those of the other methods in terms of false detection. More over, the execution time is significantly lower than that of the method ranked second in performance. For multichannel data, the problem is tackled using two approaches. First, it is assumed that the sources are periodic and the statistical characteristics of periodic sources are exploited in developing a method to effectively choose the appropriate delays in which the diagonalization takes place. In the second approach it is assumed that the sources of interest are cyclostationary. Necessary and sufficient conditions for extractability of the sources are mathematically proved and the extraction algorithms are proposed. Ballistocardiogram (BCG) artifact is considered as the sum of a number of independent cyclostationary components having the same cycle frequency. The proposed method, called cyclostationary source extraction (CSE), is able to extract these components without much destructive effect on the background electroencephalogram (EEG)
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Östlund, Nils. "Adaptive signal processing of surface electromyogram signals." Doctoral thesis, Umeå universitet, Strålningsvetenskaper, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-743.

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Electromyography is the study of muscle function through the electrical signals from the muscles. In surface electromyography the electrical signal is detected on the skin. The signal arises from ion exchanges across the muscle fibres’ membranes. The ion exchange in a motor unit, which is the smallest unit of excitation, produces a waveform that is called an action potential (AP). When a sustained contraction is performed the motor units involved in the contraction will repeatedly produce APs, which result in AP trains. A surface electromyogram (EMG) signal consists of the superposition of many AP trains generated by a large number of active motor units. The aim of this dissertation was to introduce and evaluate new methods for analysis of surface EMG signals. An important aspect is to consider where to place the electrodes during the recording so that the electrodes are not located over the zone where the neuromuscular junctions are located. A method that could estimate the location of this zone was presented in one study. The mean frequency of the EMG signal is often used to estimate muscle fatigue. For signals with low signal-to-noise ratio it is important to limit the integration intervals in the mean frequency calculations. Therefore, a method that improved the maximum frequency estimation was introduced and evaluated in comparison with existing methods. The main methodological work in this dissertation was concentrated on finding single motor unit AP trains from EMG signals recorded with several channels. In two studies single motor unit AP trains were enhanced by using filters that maximised the kurtosis of the output. The first of these studies used a spatial filter, and in the second study the technique was expanded to include filtration in time. The introduction of time filtration resulted in improved performance, and when the method was evaluated in comparison with other methods that use spatial and/or temporal filtration, it gave the best performance among them. In the last study of this dissertation this technique was used to compare AP firing rates and conduction velocities in fibromyalgia patients as compared with a control group of healthy subjects. In conclusion, this dissertation has resulted in new methods that improve the analysis of EMG signals, and as a consequence the methods can simplify physiological research projects.
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Östlund, Nils. "Adaptive signal processing of surface electromyogram signals /." Umeå : Department of Radiation Sciences, Umeå University, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-743.

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Palekar, Trishul Ajit. "Signal optimization at isolated intersections using pre-signals." Texas A&M University, 2006. http://hdl.handle.net/1969.1/4279.

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This research proposes a new signal operation strategy aimed at efficient utilization of green time by cutting down on the start up and response loss times. The idea is to have a "pre-signal" on each main approach a few hundred feet upstream of the intersection in addition to the main intersection signal, which is coordinated with the pre-signal. The offset between the main and pre-signal ensures that the majority of start up losses does not occur at the main signal. The benefits of the system under various traffic conditions were evaluated based on analysis of the queue discharge process and Corridor Simulation (CORSIM) study. The proposed measure should reduce the travel time and total control delay for the signalized network. To attain the objective the following two studies were undertaken: 1. Development of a queue discharge model to investigate the expected benefits of the system. 2. Simulation of the system: In the second part of the research, the proposed strategy was tested using CORSIM to evaluate its performance vis-à-vis the baseline case. The queue discharge model (QDM) was found to be linear in nature in contrast to prior expectations. The model was used to quantify the benefits obtained from the pre-signal system. The result of this analysis indicated that the proposed strategy would yield significant travel time savings and reductions in total control delay. In addition to the QDM analysis, CORSIM simulations were used to code various hypothetical scenarios to test the concept under various constraints and limitations. As per expectations, it was found that the system was beneficial for high demand levels and longer offsets. The upper limit on offsets was determined by visual observation of platoon dispersion and therefore the maximum offset distance was restricted to 450 feet. For scenarios where split phasing was used, the break even point in terms of demand level was found to be 2500 vph on a three lane approach, whereas that for a lag-lag type of phasing strategy was found to be 1800 vph, also on a three lane approach.
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Chan, M. K. "Adaptive signal processing algorithms for non-Gaussian signals." Thesis, Queen's University Belfast, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269023.

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Bland, Denise. "Alias-free signal processing of nonuniformly sampled signals." Thesis, University of Westminster, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.322992.

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Park, Subok. "Signal detection with random backgrounds and random signals." Diss., The University of Arizona, 2004. http://hdl.handle.net/10150/280729.

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In this dissertation we explore theoretical and computational methods to investigate Bayesian ideal observers for performing signal-detection tasks. Object models are used to take into account object variability in image backgrounds and signals for the detection tasks. In particular, lumpy backgrounds (LBs) and Gaussian signals are used for various paradigms of signal-detection tasks. Simplified pinhole imaging systems in nuclear medicine are simulated for this work. Markov-chain Monte Carlo (MCMC) methods that estimate the ideal observer test statistic, the likelihood ratio, for signal-known-exactly (SKE) tasks, where signals are nonrandom, are employed. MCMC methods are extended to signal-known-statistically (SKS) tasks, where signals are random. Psychophysical studies for the SKE and SKS tasks using non-Gaussian and Gaussian distributed LBs are conducted. The performance of the Bayesian ideal observer, the human observer, and the channelized-Hotelling observer for the SKE and SKS tasks is compared. Human efficiencies for both the SKE tasks and SKS tasks are estimated. Also human efficiencies for non-Gaussian and Gaussian-distributed LBs are compared for the SKE tasks. Finally, the theory of the channelized-ideal observer (CIO) is introduced to approximate the performance of the ideal observer by the performance of the CIO in cases where the channel outputs of backgrounds and signals are non-Gaussian distributed. Computational approaches to estimate the CIO are investigated.
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Hannaske, Roland. "Fast Digitizing and Digital Signal Processing of Detector Signals." Forschungszentrum Dresden, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:d120-qucosa-27888.

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A fast-digitizer data acquisition system recently installed at the neutron time-of-flight experiment nELBE, which is located at the superconducting electron accelerator ELBE of Forschungszentrum Dresden-Rossendorf, is tested with two different detector types. Preamplifier signals from a high-purity germanium detector are digitized, stored and finally processed. For a precise determination of the energy of the detected radiation, the moving-window deconvolution algorithm is used to compensate the ballistic deficit and different shaping algorithms are applied. The energy resolution is determined in an experiment with γ-rays from a 22Na source and is compared to the energy resolution achieved with analogously processed signals. On the other hand, signals from the photomultipliers of barium fluoride and plastic scintillation detectors are digitized. These signals have risetimes of a few nanoseconds only. The moment of interaction of the radiation with the detector is determined by methods of digital signal processing. Therefore, different timing algorithms are implemented and tested with data from an experiment at nELBE. The time resolutions achieved with these algorithms are compared to each other as well as to reference values coming from analog signal processing. In addition to these experiments, some properties of the digitizing hardware are measured and a program for the analysis of stored, digitized data is developed. The analysis of the signals shows that the energy resolution achieved with the 10-bit digitizer system used here is not competitive to a 14-bit peak-sensing ADC, although the ballistic deficit can be fully corrected. However, digital methods give better result in sub-ns timing than analog signal processing.
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Books on the topic "Signals"

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Lessard, Charles S. Signal Processing of Random Physiological Signals. Cham: Springer International Publishing, 2006. http://dx.doi.org/10.1007/978-3-031-01610-3.

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Signal processing: Signals, filtering, and detection. New York: Van Nostrand Reinhold, 1987.

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Hall, Diane. Signals. London: Lingual House, 1988.

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Bard, Perry. Signals. Edited by QCC Art Gallery. Bayside, N.Y: Queensborough Community College, 1989.

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Copyright Paperback Collection (Library of Congress), ed. Signals. New York: Ace Books, 2003.

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Signals. Columbia, S.C: University of South Carolina Press, 2008.

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Palme, Klaus, ed. Signals and Signal Transduction Pathways in Plants. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-0239-1.

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Discrete random signals and statistical signal processing. Englewood Cliffs, NJ: Prentice Hall, 1992.

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Hucknall, D. J. Signals and signal-boxes of Great Britain. Phoenix Mill, Thrupp, Stroud, Gloucestershire: Sutton Pub., 1998.

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Klaus, Palme, ed. Signals and signal transduction pathways in plants. Dordrecht: Kluwer Academic Publishers, 1994.

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Book chapters on the topic "Signals"

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Mazor, Stanley, and Patricia Langstraat. "Signals & Signal Assignments." In A Guide to VHDL, 105–35. Boston, MA: Springer US, 1992. http://dx.doi.org/10.1007/978-1-4757-2114-0_5.

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Wang, K. C. "Signals and Signal Processing." In Systems Programming in Unix/Linux, 205–19. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92429-8_6.

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Wang, K. C. "Signals and Signal Processing." In Design and Implementation of the MTX Operating System, 257–71. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17575-1_9.

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Mazor, Stanley, and Patricia Langstraat. "Signals & Signal Assignments." In A Guide to VHDL, 109–39. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/978-1-4615-3216-3_5.

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Cohen Tenoudji, Frédéric. "Causal Signals—Analytic Signals." In Modern Acoustics and Signal Processing, 177–205. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42382-1_11.

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Morgan, Michael M., MacDonald J. Christie, Luis De Lecea, Jason C. G. Halford, Josee E. Leysen, Warren H. Meck, Catalin V. Buhusi, et al. "Signals." In Encyclopedia of Psychopharmacology, 1237. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_4540.

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Usher, M. J., and C. G. Guy. "Signals." In Information and Communication for Engineers, 35–92. London: Macmillan Education UK, 1997. http://dx.doi.org/10.1007/978-1-349-13477-9_2.

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Robinson, Michael. "Signals." In Topological Signal Processing, 39–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-36104-3_3.

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Maston, Gregory A., Tony R. Taylor, and Julie N. Villar. "Signals." In Elements of STIL, 33–57. Boston, MA: Springer US, 2003. http://dx.doi.org/10.1007/978-1-4615-0463-4_3.

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Silvis-Cividjian, Natalia. "Signals." In Undergraduate Topics in Computer Science, 15–30. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51655-4_2.

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Conference papers on the topic "Signals"

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Rutenbar, Rob A., David Harame, Kurt Johnson, Paul Kempf, Teresa Meng, Reza Rofougaran, and James Spoto. "Mixed signals on mixed-signal." In the 40th conference. New York, New York, USA: ACM Press, 2003. http://dx.doi.org/10.1145/775832.775904.

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Blundell, V., T. Clarke, and D. Williams. "Synthetic signals for signal processing." In Sensor Signal Processing for Defence (SSPD 2010). IET, 2010. http://dx.doi.org/10.1049/ic.2010.0229.

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Tataronis, John, and Bahaa E. A. Saleh. "Phase conjugation of nonstationary optical signals." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1986. http://dx.doi.org/10.1364/oam.1986.fw5.

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The generation of phase conjugated replicas of optical signals has been the subject of many theoretical and experimental studies. Phase conjugation of harmonic signals is a byproduct of certain nonlinear processes such as degenerate four- wave mixing and stimulated Brillouin scattering. Although conjugation of steady signals is well established, the possibility and the effectiveness of conjugating unsteady signals remain largely unexplored. When the envelope of an optical signal varies, new physical phenomena in the conjugation process arise. As previously shown,1 dispersion in the conjugation process distorts the phase conjugate replica of a pulsed signal. Distortion appears even if the response of the medium to the applied optical signal is instantaneous.
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Assaleh, Khaled T., and Richard J. Mammone. "Signal-adaptive decomposition of multicomponent signals." In SPIE's 1993 International Symposium on Optics, Imaging, and Instrumentation, edited by Franklin T. Luk. SPIE, 1993. http://dx.doi.org/10.1117/12.160441.

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Minasian, R. A., E. H. W. Chan, and Xiaoke Yi. "Photonic signal processing of microwave signals." In 35th Australian Conference on Optical Fibre Technology (ACOFT 2010). IEEE, 2010. http://dx.doi.org/10.1109/acoft.2010.5929926.

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Ashtari, Ali, Gabriel Thomas, Hector Garces, and Benjamin C. Flores. "Radar signal design using chaotic signals." In 2007 International Waveform Diversity and Design Conference. IEEE, 2007. http://dx.doi.org/10.1109/wddc.2007.4339442.

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Katz, A., X. J. Lu, E. G. Kanterikis, Yao Li, Yan Zhang, and N. P. Caviris. "Real-time optoelectronic Gabor detection of transient signals." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.ml6.

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Detection of transient signals in a noisy environment is an important topic in radar, sonar, and communications. An optoelectronic system for detection of transient signals has been constructed. The detection scheme is based on the Gabor representation of a signal, which can be used to represent transient signals of unknown shape and arrival time. The transient signal and Gabor window function are written to the laser beam profile via either transparency or spatial light modulator. The Gabor coefficients are detected by a 2-D CCD array. The use of a liquid crystal television, allowing for real-time detection of signals is investigated. Experimental results for exponentially decaying signals, are presented which clearly indicate the signal frequency and arrival time.
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Kalbfleisch, Paul, Svenja Horn, and Monika Ivantysynova. "Cyclostationary Analysis of Measured Pump Acoustic and Vibration Signals." In BATH/ASME 2018 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/fpmc2018-8899.

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The stationary signal assumption is convenient as its signal processing methods are the minimum effort required to characterize periodic signals and therefore the most common. However, signals from rotating machines have been found to naturally be characterized as cyclostationary. The existent of natural phenomenon such as, shaft imbalances, turbulent fluid flows, friction, combustion forces, and torsional vibrations create modulation effects, that can be seen in the measured signals. These observed modulations in pump noise and vibration signals are synonymous to amplitude modulations (AM), frequency modulations (FM), and potentially phase modulations in electrical systems. Having this knowledge, the fluid power noise, vibration, and harshness (NVH) researchers can draw from an enormous amount of progress made in the modern telecommunication signal processing methods of cyclostationary signals. This article introduces the basic concepts of cyclostationary signals, some of their signal processing techniques, and a simple example of analysis for a positive displacement machine through the cyclostationary paradigm.
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Pagot, J.-B., P. Thevenon, O. Julien, Francisco Amarillo-Fernandez, and Denis Maillard. "Signal Quality Monitoring for New GNSS Signals." In 29th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2016). Institute of Navigation, 2016. http://dx.doi.org/10.33012/2016.14862.

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Amma, Christoph, Hannes Volk, and Tanja Schultz. "Compressed signal representation for inertial sensor signals." In UbiComp '13: The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2494091.2494140.

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Reports on the topic "Signals"

1

Green, David M. Complex Auditory Signals. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada199832.

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Green, David M. Complex Auditory Signals. Fort Belvoir, VA: Defense Technical Information Center, February 1994. http://dx.doi.org/10.21236/ada278391.

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Green, David M. Complex Auditory Signals. Fort Belvoir, VA: Defense Technical Information Center, December 1992. http://dx.doi.org/10.21236/ada261491.

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Kamath, C., and I. Fodor. Separation of Climate Signals. Office of Scientific and Technical Information (OSTI), November 2002. http://dx.doi.org/10.2172/15002083.

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Ruffa, Anthony A. Simultaneous Continuous Wave Signals. Fort Belvoir, VA: Defense Technical Information Center, September 2015. http://dx.doi.org/10.21236/ad1003799.

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Gardner, William A. Workshop on Cyclostationary Signals. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada266112.

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Papanicolaou, George C. Signals, Waves and Transport. Fort Belvoir, VA: Defense Technical Information Center, January 2001. http://dx.doi.org/10.21236/ada388642.

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Hardie, T., ed. Transport Protocol Path Signals. RFC Editor, April 2019. http://dx.doi.org/10.17487/rfc8558.

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Halford, Donald. Transparent metrology of signal to noise ratios of noisy band-limited digital signals. Gaithersburg, MD: National Bureau of Standards, 1985. http://dx.doi.org/10.6028/nbs.tn.1077.

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Lauchle, Gerald C., Nathan K. Naluai, and Thomas B. Gabrielson. Intensity Processing of DIFAR Signals. Fort Belvoir, VA: Defense Technical Information Center, September 2005. http://dx.doi.org/10.21236/ada444386.

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