Academic literature on the topic 'Signal behavior'
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Journal articles on the topic "Signal behavior"
Wang, Faya. "Multipacting electron signal behavior." Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment 698 (January 2013): 147–51. http://dx.doi.org/10.1016/j.nima.2012.09.056.
Full textLi, Xianfeng, Sen Xu, and Xiaopeng Hua. "Pattern Recognition of Grating Perimeter Intrusion Behavior in Deep Learning Method." Symmetry 13, no. 1 (January 6, 2021): 87. http://dx.doi.org/10.3390/sym13010087.
Full textde Pedro-Carracedo, Javier, Ana María Ugena, and Ana Pilar Gonzalez-Marcos. "Dynamical Analysis of Biological Signals with the 0–1 Test: A Case Study of the PhotoPlethysmoGraphic (PPG) Signal." Applied Sciences 11, no. 14 (July 15, 2021): 6508. http://dx.doi.org/10.3390/app11146508.
Full textZhang, Feng, Yi Nong Li, and Lei Wang. "Behavior Analysis of FxLMS Based on Deterministic Signal." Advanced Materials Research 403-408 (November 2011): 3262–66. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3262.
Full textAnderson, Christopher, Amanda Zimmerman, Skylar Lewis, John Marmion, and Jeanette Gustat. "Patterns of Cyclist and Pedestrian Street Crossing Behavior and Safety on an Urban Greenway." International Journal of Environmental Research and Public Health 16, no. 2 (January 12, 2019): 201. http://dx.doi.org/10.3390/ijerph16020201.
Full textAkassou, Imane, Sabina Avosani, Valentina Caorsi, Vincenzo Verrastro, Marco Ciolli, and Valerio Mazzoni. "Intrasexual Vibrational Behavior of Philaenus spumarius in Semi-Field Conditions." Insects 12, no. 7 (June 28, 2021): 584. http://dx.doi.org/10.3390/insects12070584.
Full textLi, Haitao, Xiang Chen, Yingke Lei, Pengcheng Li, and Caiyi Lou. "Identification of Shortwave Radio Communication Behavior Based on Autocorrelation Spectrogram Features." Wireless Communications and Mobile Computing 2022 (September 22, 2022): 1–14. http://dx.doi.org/10.1155/2022/8614952.
Full textYu, Ke, and Huapu Lu. "Effects of Countdown Signals in Red Phase on Drivers: A Comparative Study between Japan and Turkey." Mathematical Problems in Engineering 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/671589.
Full textDin, Zia Ud, and Leonhard E. Bernold. "Experimental study of signal behavior for wireless communication in construction." Construction Innovation 17, no. 4 (October 20, 2017): 475–91. http://dx.doi.org/10.1108/ci-11-2016-0061.
Full textGlaudas, Xavier, and Christopher T. Winne. "Do warning displays predict striking behavior in a viperid snake, the cottonmouth (Agkistrodon piscivorus)?" Canadian Journal of Zoology 85, no. 4 (April 2007): 574–78. http://dx.doi.org/10.1139/z07-025.
Full textDissertations / Theses on the topic "Signal behavior"
Elmitiny, Noor. "Providing a Better Understanding for the Motorist Behavior Towards Signal Change." Doctoral diss., University of Central Florida, 2009. http://digital.library.ucf.edu/cdm/ref/collection/ETD/id/4264.
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Department of Civil and Environmental Engineering
Engineering and Computer Science
Civil Engineering PhD
Jai, Wun Hoa Arthur. "Underwater acoustic signal behavior prediction in the region of Kauai Island." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/33582.
Full textIncludes bibliographical references (p. 175-176).
Behavior of underwater sound propagation over long-ranges has been studied for several decades. The purpose of this is to describe sound propagation phenomena in various ocean environments. The key to understanding and visualizing is mathematical modeling. In the ocean acoustics community, four major mathematical techniques have been commonly used to model behavior of acoustic signal in the ocean environment. And they can be categorized into two different fields, range-independent and range-dependent. The accuracy of each method is depends on the environment characteristics. Since the propagating signal can be characterized through the mathematical modeling, it is then possible to use the propagating signal to perform beamforming and determine the characteristic of beam output.
by Wun Hoa Arthur Jai.
S.M.
Glaser, John Stanley 1964. "Topics in large-signal behavior of power electronic converters and systems." Diss., The University of Arizona, 1996. http://hdl.handle.net/10150/282217.
Full textPhillips, Catherine T. Johnston Carol Eileen. "Evolution of signal divergence and behavior in Cyprinella galactura, the whitetail shiner." Auburn, Ala., 2006. http://repo.lib.auburn.edu/2006%20Fall/Dissertations/PHILLIPS_CATHERINE_27.pdf.
Full textAl-Mudhaffar, Azhar. "Impacts of Traffic Signal Control Strategies." Doctoral thesis, Stockholm : Division of transports and logistics, Royal Institute of Technology, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-4268.
Full textDrake, Daniel F. "Information's role in the estimation of chaotic signals." Diss., Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/14793.
Full textMcKay, Ailsa J. "Central vasopressin signalling and aggressive behaviour." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/4194.
Full textSaggese, Alessia. "Detecting and indexing moving objects for behavior analysis by video and audio interpretation." Doctoral thesis, Caen, 2014. http://www.theses.fr/2014CAEN2021.
Full textIn the last decades we have assisted to a growing need for security in many public environments. The main limitation of this traditional audio-video surveillance systems lies in the so called psychological overcharge issue of the human operators responsible for security, that causes a decrease in their capabilities to analyse raw data flows from multiple sources of multimedia information. For the above mentioned reasons, in this thesis we propose an intelligent surveillance system able to provide images and video with a semantic interpretation, for trying to bridge the gap between their low-level representation in terms of pixels, and the high-level, natural language description that a human would give about them. In particular, the proposed framework starts by analysing the videos and by extracting the trajectories of the objects populating the scene. Once extracted, this large amount of trajectories needs to be indexed and properly stored in order to improve the overall performance of the system during the retrieving. Furthermore, the human operator is informed as soon as an abnormal behaviour occurs. Whereas the information extracted from the videos are not sufficient or not sufficiently reliable, the proposed system in enriched by a module in charge of recognizing audio events, such as shoots, screams or broken glasses. Each proposed module has been tested both over standard datasets and in real environments; the promising obtained results confirm the advance with respect to the state of the art, as well as the applicability of the proposed method in real scenarios
Lee, Chungyong. "Noise reduction methods for chaotic signals with application to secure communications." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/14823.
Full textLarsson, Petter. "Automatic Visual Behavior Analysis." Thesis, Linköping University, Department of Electrical Engineering, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-1980.
Full textThis work explores the possibilities of robust, noise adaptive and automatic segmentation of driver eye movements into comparable quantities as defined in the ISO 15007 and SAE J2396 standards for in-vehicle visual demand measurements. Driver eye movements have many potential applications, from the detection of driver distraction, drowsiness and mental workload, to the optimization of in-vehicle HMIs. This work focuses on SeeingMachines head and eye-tracking system SleepyHead (or FaceLAB), but is applicable to data from other similar eye-tracking systems. A robust and noise adaptive hybrid algorithm, based on two different change detection protocols and facts about eye-physiology, has been developed. The algorithm has been validated against data, video transcribed according to the ISO/SAE standards. This approach was highly successful, revealing correlations in the region of 0.999 between analysis types i.e. video transcription and the analysis developed in this work. Also, a real-time segmentation algorithm, with a unique initialization fefature, has been developed and validated based on the same approach.
This work enables real-time in-vehicle systems, based on driver eye-movements, to be developed and tested in real driving conditions. Furthermore, it has augmented FaceLAB by providing a tool that can easily be used when analysis of eye movements are of interest e.g. HMI and ergonomics studies, analysis of warnings, driver workload estimation etc.
Books on the topic "Signal behavior"
Takeda, Kazuya, Hakan Erdogan, John H. L. Hansen, and Huseyin Abut, eds. In-Vehicle Corpus and Signal Processing for Driver Behavior. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-79582-9.
Full textB, Hoek Jan, and National Institute on Alcohol Abuse and Alcoholism (U.S.), eds. Ethanol and intracellular signaling: From molecules to behavior. Bethesda, MD (6000 Executive Blvd., Bethesda 20892): U.S. Dept. of Health and Human Services, Public Health Service, National Institutes of Health, National Institute on Alcohol Abuse and Alcoholism, 2000.
Find full textR, Buchler J., and Kandrup Henry E, eds. Nonlinear signal and image analysis. New York, N.Y: New York Academy of Sciences, 1997.
Find full textHoek, Jan B. Ethanol and intracellular signaling: From molecules to behavior. Bethesda, MD (6000 Executive Boulevard, Bethesda, 20892): U.S. Department of Health and Human Services, Public Health Service, National Institute of Health, National Institute on Alcohol Abuse and Alcoholism, 2000.
Find full text1981-, Lin W. Sabrina, and Liu, K. J. Ray, 1961-, eds. Behavior dynamics in media-sharing social networks. Cambridge: Cambridge University Press, 2011.
Find full textKong, Tse Chi, ed. Reconstruction of chaotic signals with applications to chaos-based communications. [Beijing, China]: Tsinghua University Press, 2008.
Find full text1966-, Gao Jianbo, ed. Multiscale analysis of complex time series: Integration of chaos and random fractal theory, and beyond. Hoboken, NJ: John Wiley & Sons, 2007.
Find full textA, Velastin Sergio, Remagnino Paolo 1963-, and Institution of Electrical Engineers, eds. Intelligent distributed video surveillance systems. London: Institution of Electrical Engineers, 2006.
Find full textInternational Society for Invertebrate Neurobiology. Symposium. Neurobiology of invertebrates: Signal molecules, networks, behaviour. Budapest: Akadémiai Kiadó, 1993.
Find full textR, Dillon C., ed. Signals and systems: Models and behaviour. Wokingham: Van Nostrand Reinhold, 1986.
Find full textBook chapters on the topic "Signal behavior"
Getty, Thomas, Alan C. Kamil, and Pamela G. Real. "Signal Detection Theory and Foraging for Cryptic or Mimetic Prey." In Foraging Behavior, 525–48. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1839-2_18.
Full textKorinšek, Gašper, Tadej Tuma, and Meta Virant-Doberlet. "Automated Vibrational Signal Recognition and Playback." In Biotremology: Studying Vibrational Behavior, 149–73. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22293-2_9.
Full textLussu, Vincenzo, Radoslaw Niewiadomski, Gualtiero Volpe, and Antonio Camurri. "Using the Audio Respiration Signal for Multimodal Discrimination of Expressive Movement Qualities." In Human Behavior Understanding, 102–15. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46843-3_7.
Full textPalmieri, Igor, Luiz H. A. Monteiro, and Maria D. Miranda. "The Neuronal Signal and Its Models." In Computational Models of Brain and Behavior, 519–30. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119159193.ch38.
Full textDunlop, Rebecca, William L. Gannon, Marthe Kiley-Worthington, Peggy S. M. Hill, Andreas Wessel, and Jeanette A. Thomas. "Vibrational and Acoustic Communication in Animals." In Exploring Animal Behavior Through Sound: Volume 1, 389–417. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97540-1_11.
Full textSato, K., and K. Touhara*. "Insect Olfaction: Receptors, Signal Transduction, and Behavior." In Results and Problems in Cell Differentiation, 203–20. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/400_2008_10.
Full textOberst, Sebastian, Joseph C. S. Lai, and Theodore A. Evans. "Physical Basis of Vibrational Behaviour: Channel Properties, Noise and Excitation Signal Extraction." In Biotremology: Studying Vibrational Behavior, 53–78. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22293-2_5.
Full textZhang, Xinpeng. "Behavior Steganography in Social Network." In Advances in Intelligent Information Hiding and Multimedia Signal Processing, 21–23. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-50209-0_3.
Full textErber, Jochen, and Uwe Homberg. "Neural Signal Processing in the Median Protocerebrum of the Bee." In Neurobiology and Behavior of Honeybees, 253–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 1987. http://dx.doi.org/10.1007/978-3-642-71496-2_21.
Full textErbe, Christine, Alec Duncan, Lauren Hawkins, John M. Terhune, and Jeanette A. Thomas. "Introduction to Acoustic Terminology and Signal Processing." In Exploring Animal Behavior Through Sound: Volume 1, 111–52. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97540-1_4.
Full textConference papers on the topic "Signal behavior"
Bar-Gera, Hillel, Edna Schechtman, Tal Ze'evi, and Oren Musicant. "Yellow Signal Driver Crossing Behavior." In 2015 IEEE 18th International Conference on Intelligent Transportation Systems - (ITSC 2015). IEEE, 2015. http://dx.doi.org/10.1109/itsc.2015.440.
Full textFugger, Thomas F., Bryan C. Randles, Jesse L. Wobrock, Anthony C. Stein, and William C. Whiting. "Pedestrian Behavior at Signal-Controlled Crosswalks." In SAE 2001 World Congress. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2001. http://dx.doi.org/10.4271/2001-01-0896.
Full textUsher, Colin T., Wayne Daley, Bruce Webster, and Casey Ritz. "Signal processing for animal behavior detection." In 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2014. http://dx.doi.org/10.1109/globalsip.2014.7032301.
Full textLi, Jinchao, Sheng-Yuan Tu, and Ali H. Sayed. "Honeybee swarming behavior using diffusion adaptation." In 2011 Digital Signal Processing and Signal Processing Education Meeting (DSP/SPE). IEEE, 2011. http://dx.doi.org/10.1109/dsp-spe.2011.5739220.
Full textVelarde, Manuel G. "Anharmonicity, neural-like lattices, and fast signal/electric transmission." In COOPERATIVE BEHAVIOR IN NEURAL SYSTEMS: Ninth Granada Lectures. AIP, 2007. http://dx.doi.org/10.1063/1.2709598.
Full textMejías, Jorge F., and Joaquín J. Torres. "Signal detection in networks of spiking neurons with dynamical synapses." In COOPERATIVE BEHAVIOR IN NEURAL SYSTEMS: Ninth Granada Lectures. AIP, 2007. http://dx.doi.org/10.1063/1.2709589.
Full textNozari, Sheida, Ali Krayani, Lucio Marcenaro, David Martin, and Carlo Regazzoni. "Incremental Learning through Probabilistic Behavior Prediction." In 2022 30th European Signal Processing Conference (EUSIPCO). IEEE, 2022. http://dx.doi.org/10.23919/eusipco55093.2022.9909735.
Full textAl-Hamadi, Hussam, Amjad Gawanmeh, and Mahmoud Al-Qutayri. "Formalizing electrocardiogram (ECG) signal behavior in event-B." In 2014 IEEE 16th International Conference on e-Health Networking, Applications and Services (Healthcom 2014). IEEE, 2014. http://dx.doi.org/10.1109/healthcom.2014.7001813.
Full textWang, Lei, Baoyu Zheng, Jingwu Cui, and Wenjing Yue. "Spectrum sensing using non-asymptotic behavior of eigenvalues." In Signal Processing (WCSP 2011). IEEE, 2011. http://dx.doi.org/10.1109/wcsp.2011.6096917.
Full textZhao, Zhe, Fei Gao, Hanyue Li, Yimin Li, and Haikun Luo. "A mixed behavior/structural model for analog LDPC decoders including mismatch effects and dynamic behavior." In 2015 International Conference on Wireless Communications & Signal Processing (WCSP). IEEE, 2015. http://dx.doi.org/10.1109/wcsp.2015.7341182.
Full textReports on the topic "Signal behavior"
Cameron, P., and M. Morvillo. Thermal Behavior of RHIC BPM Cryogenic Signal Cables. Office of Scientific and Technical Information (OSTI), January 1996. http://dx.doi.org/10.2172/1119462.
Full textBrown Horowitz, Sigal, Eric L. Davis, and Axel Elling. Dissecting interactions between root-knot nematode effectors and lipid signaling involved in plant defense. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598167.bard.
Full textAbbott, Joshua, H. Allen Klaiber, and V. Kerry Smith. Economic Behavior, Market Signals, and Urban Ecology. Cambridge, MA: National Bureau of Economic Research, February 2015. http://dx.doi.org/10.3386/w20959.
Full textWakita, Toshihiro, Koji Ozawa, Chiyomi Miyajima, Kei Igarashi, Katsunobu Ito, Kazuya Takeda, and Fumitada Itakura. Study on Driver Identification Method Using Driving Behavior Signals. Warrendale, PA: SAE International, September 2005. http://dx.doi.org/10.4271/2005-08-0569.
Full textTaylor, Oliver-Denzil, Amy Cunningham,, Robert Walker, Mihan McKenna, Kathryn Martin, and Pamela Kinnebrew. The behaviour of near-surface soils through ultrasonic near-surface inundation testing. Engineer Research and Development Center (U.S.), September 2021. http://dx.doi.org/10.21079/11681/41826.
Full textAburto, A., D. J. Rountry, and J. L. Danzer. Behavioral Response of Blue Whales to Active Signals. Fort Belvoir, VA: Defense Technical Information Center, June 1997. http://dx.doi.org/10.21236/ada328274.
Full textFinley, Dorothy L. Tactical Communications Research and Development Requirements from Signal and Behavioral Science Perspectives. Fort Belvoir, VA: Defense Technical Information Center, June 1997. http://dx.doi.org/10.21236/ada337680.
Full textHouser, Dorian S., James J. Finneran, and Laura Yates. Behavioral Response of Dolphins to Signals Simulating Mid-Frequency Sonar. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541587.
Full textHolladay, J. Scott, Jacob LaRiviere, David Novgorodsky, and Michael Price. Asymmetric Effects of Non-Pecuniary Signals on Search and Purchase Behavior for Energy-Efficient Durable Goods. Cambridge, MA: National Bureau of Economic Research, December 2016. http://dx.doi.org/10.3386/w22939.
Full textTyack, Peter L. 3S2-Behavioral Response Studies of Cetaceans to Naval Signals in Norwegian Waters. Fort Belvoir, VA: Defense Technical Information Center, September 2010. http://dx.doi.org/10.21236/ada541470.
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