Relevant bibliographies by topics / Statistical Signal Processing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Statistical Signal Processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 March 2023

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Journal articles on the topic "Statistical Signal Processing"

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Ray, W. D., Edward J. Wegman, and James G. Smith. "Statistical Signal Processing." Journal of the Royal Statistical Society. Series A (General) 148, no. 1 (1985): 63. http://dx.doi.org/10.2307/2981518.

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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.

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Ottersten, Björn, Torsten Söderström, and Bo Wahlberg. "Statistical signal processing and control." Automatica 30, no. 1 (January 1994): 9. http://dx.doi.org/10.1016/0005-1098(94)90224-0.

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Woolfson, M. S. "Book Review: Discrete Random Signals and Statistical Signal Processing." International Journal of Electrical Engineering & Education 30, no. 1 (January 1993): 94. http://dx.doi.org/10.1177/002072099303000125.

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Liu, Shin Ta. "Nonlinear Signal Processing: A Statistical Approach." Technometrics 48, no. 1 (February 2006): 148–49. http://dx.doi.org/10.1198/tech.2006.s355.

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Caby, Errol C. "An Introduction to Statistical Signal Processing." Technometrics 48, no. 4 (November 2006): 572–73. http://dx.doi.org/10.1198/tech.2006.s436.

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Riedi, Rudolf H. "An Introduction to Statistical Signal Processing." Journal of the American Statistical Association 101, no. 475 (September 2006): 1317. http://dx.doi.org/10.1198/jasa.2006.s133.

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Kameoka, Hirokazu. "1. Music and Statistical Signal Processing." Journal of The Institute of Image Information and Television Engineers 71, no. 7 (2017): 452–56. http://dx.doi.org/10.3169/itej.71.452.

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Potters, Marc, and William Bialek. "Statistical mechanics and visual signal processing." Journal de Physique I 4, no. 11 (November 1994): 1755–75. http://dx.doi.org/10.1051/jp1:1994219.

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Gruber, Marvin H. J. "Statistical Digital Signal Processing and Modeling." Technometrics 39, no. 3 (August 1997): 335–36. http://dx.doi.org/10.1080/00401706.1997.10485128.

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Dissertations / Theses on the topic "Statistical Signal Processing"

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Zhao, Wentao. "Genomic applications of statistical signal processing." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2952.

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Vollgraf, Roland. "Unsupervised learning methods for statistical signal processing." [S.l.] : [s.n.], 2006. http://opus.kobv.de/tuberlin/volltexte/2007/1488.

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Eng, Frida. "Non-Uniform Sampling in Statistical Signal Processing." Doctoral thesis, Linköping : Department of Electrical Engineering, Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8480.

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Bornn, Luke. "Statistical solutions for and from signal processing." Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/5345.

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With the wide range of fields engaging in signal processing research, many methods do not receive adequate dissemination across disciplines due to differences in jargon, notation, and level of rigor. In this thesis, I attempt to bridge this gap by applying two statistical techniques originating in signal processing to fields for which they were not originally intended. Firstly, I employ particle filters, a tool used for state estimation in the physics signal processing world, for the task of prior sensitivity analysis and cross validation in Bayesian statistics. Secondly, I demonstrate the application of support vector forecasters, a tool used for forecasting in the machine learning signal processing world, to the field of structural health monitoring.
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Sallee, Philip Andrew. "Statistical methods for image and signal processing /." For electronic version search Digital dissertations database. Restricted to UC campuses. Access is free to UC campus dissertations, 2004. http://uclibs.org/PID/11984.

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Xu, Cuichun. "Statistical processing on radar, sonar, and optical signals /." View online ; access limited to URI, 2008. http://0-digitalcommons.uri.edu.helin.uri.edu/dissertations/AAI3328735.

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Kuchler, Ryan J. "Theory of multirate statistical signal processing and applications." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Sep%5FKuchler%5FPhD.pdf.

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Vigoda, Benjamin William 1973. "Continuous-time analog circuits for statistical signal processing." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/62962.

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Thesis (Ph. D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2003.
Vita.
Includes bibliographical references (p. 205-209).
This thesis proposes an alternate paradigm for designing computers using continuous-time analog circuits. Digital computation sacrifices continuous degrees of freedom. A principled approach to recovering them is to view analog circuits as propagating probabilities in a message passing algorithm. Within this framework, analog continuous-time circuits can perform robust, programmable, high-speed, low-power, cost-effective, statistical signal processing. This methodology will have broad application to systems which can benefit from low-power, high-speed signal processing and offers the possibility of adaptable/programmable high-speed circuitry at frequencies where digital circuitry would be cost and power prohibitive. Many problems must be solved before the new design methodology can be shown to be useful in practice: Continuous-time signal processing is not well understood. Analog computational circuits known as "soft-gates" have been previously proposed, but a complementary set of analog memory circuits is still lacking. Analog circuits are usually tunable, rarely reconfigurable, but never programmable. The thesis develops an understanding of the convergence and synchronization of statistical signal processing algorithms in continuous time, and explores the use of linear and nonlinear circuits for analog memory. An exemplary embodiment called the Noise Lock Loop (NLL) using these design primitives is demonstrated to perform direct-sequence spread-spectrum acquisition and tracking functionality and promises order-of-magnitude wins over digital implementations. A building block for the construction of programmable analog gate arrays, the "soft-multiplexer" is also proposed.
by Benjamin Vigoda.
Ph.D.
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Vallet, Pascal. "Random matrices and applications to statistical signal processing." Thesis, Paris Est, 2011. http://www.theses.fr/2011PEST1055/document.

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Dans cette thèse, nous considérons le problème de la localisation de source dans les grands réseaux de capteurs, quand le nombre d'antennes du réseau et le nombre d'échantillons du signal observé sont grands et du même ordre de grandeur. Nous considérons le cas où les signaux source émis sont déterministes, et nous développons un algorithme de localisation amélioré, basé sur la méthode MUSIC. Pour ce faire, nous montrons de nouveaux résultats concernant la localisation des valeurs propres des grandes matrices aléatoires gaussiennes complexes de type information plus bruit
In this thesis, we consider the problem of source localization in large sensor networks, when the number of antennas of the network and the number of samples of the observed signal are large and of the same order of magnitude. We also consider the case where the source signals are deterministic, and we develop an improved algorithm for source localization, based on the MUSIC method. For this, we fist show new results concerning the position of the eigen values of large information plus noise complex gaussian random matrices
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Palladini, Alessandro <1981&gt. "Statistical methods for biomedical signal analysis and processing." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2009. http://amsdottorato.unibo.it/1358/1/palladini_alessandro_tesi.pdf.

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Statistical modelling and statistical learning theory are two powerful analytical frameworks for analyzing signals and developing efficient processing and classification algorithms. In this thesis, these frameworks are applied for modelling and processing biomedical signals in two different contexts: ultrasound medical imaging systems and primate neural activity analysis and modelling. In the context of ultrasound medical imaging, two main applications are explored: deconvolution of signals measured from a ultrasonic transducer and automatic image segmentation and classification of prostate ultrasound scans. In the former application a stochastic model of the radio frequency signal measured from a ultrasonic transducer is derived. This model is then employed for developing in a statistical framework a regularized deconvolution procedure, for enhancing signal resolution. In the latter application, different statistical models are used to characterize images of prostate tissues, extracting different features. These features are then uses to segment the images in region of interests by means of an automatic procedure based on a statistical model of the extracted features. Finally, machine learning techniques are used for automatic classification of the different region of interests. In the context of neural activity signals, an example of bio-inspired dynamical network was developed to help in studies of motor-related processes in the brain of primate monkeys. The presented model aims to mimic the abstract functionality of a cell population in 7a parietal region of primate monkeys, during the execution of learned behavioural tasks.
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Books on the topic "Statistical Signal Processing"

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Chonavel, Thierry. Statistical Signal Processing. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0139-0.

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Nandi, Swagata, and Debasis Kundu. Statistical Signal Processing. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6280-8.

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Kundu, Debasis, and Swagata Nandi. Statistical Signal Processing. India: Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0628-6.

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

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Arce, Gonzalo R. Nonlinear signal processing: A statistical approach. Hoboken, N.J: Wiley-Interscience, 2005.

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Veloni, Anastasia, Nikolaos I. Miridakis, and Erysso Boukouvala. Digital and Statistical Signal Processing. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, 2018.: CRC Press, 2018. http://dx.doi.org/10.1201/9780429507526.

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Spagnolini, Umberto. Statistical Signal Processing in Engineering. Chichester, UK: John Wiley & Sons, Ltd, 2018. http://dx.doi.org/10.1002/9781119294016.

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Swagata, Nandi, and SpringerLink (Online service), eds. Statistical Signal Processing: Frequency Estimation. India: Springer India, 2012.

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Kay, Steven M. Fundamentals of statistical signal processing. Upper Saddle River,NJ: Prentice-Hall, 1998.

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B, Ottersten, Söderström Torsten, and Wahlberg B, eds. Statistical signal processing and control. Oxford: Pergamon, 1994.

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Book chapters on the topic "Statistical Signal Processing"

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Abraham, Douglas A. "Statistical Signal Processing." In Modern Acoustics and Signal Processing, 307–46. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-92983-5_6.

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Parthasarathy, Harish. "Statistical Signal Processing." In Classical and Quantum Information Theory for the Physicist, 47–65. London: CRC Press, 2022. http://dx.doi.org/10.1201/9781003353454-6.

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Sullivan, Edmund J. "Statistical Signal Processing." In Handbook of Signal Processing in Acoustics, 1695–721. New York, NY: Springer New York, 2008. http://dx.doi.org/10.1007/978-0-387-30441-0_94.

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Kundu, Debasis. "Statistical Signal Processing." In International Encyclopedia of Statistical Science, 1466–68. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_552.

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Gopi, E. S. "Statistical Signal Processing." In Multi-Disciplinary Digital Signal Processing, 147–75. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-57430-1_5.

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Apte, Shaila Dinkar. "Statistical Speech Processing." In Random Signal Processing, 285–311. Boca Raton : CRC Press, 2018.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315155357-7.

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Nandi, Swagata, and Debasis Kundu. "Chirp Signal Model." In Statistical Signal Processing, 179–216. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6280-8_9.

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Sullivan, Edmund J. "Statistical Signal Processing Overview." In SpringerBriefs in Physics, 27–49. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-17557-7_3.

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Nandi, Swagata, and Debasis Kundu. "Introduction." In Statistical Signal Processing, 1–7. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6280-8_1.

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Nandi, Swagata, and Debasis Kundu. "Random Amplitude Sinusoidal and Chirp Model." In Statistical Signal Processing, 217–37. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6280-8_10.

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Conference papers on the topic "Statistical Signal Processing"

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"Session TP5a: Statistical signal processing for neural signals." In 2010 44th Asilomar Conference on Signals, Systems and Computers. IEEE, 2010. http://dx.doi.org/10.1109/acssc.2010.5757757.

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"Session TA8a1: Statistical signal processing." In 2017 51st Asilomar Conference on Signals, Systems, and Computers. IEEE, 2017. http://dx.doi.org/10.1109/acssc.2017.8335446.

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"Session WA5: Statistical signal processing." In 2010 44th Asilomar Conference on Signals, Systems and Computers. IEEE, 2010. http://dx.doi.org/10.1109/acssc.2010.5757882.

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Kyprianou, Ross, Peter Schachte, and Bill Moran. "Dauphin: A Signal Processing Language - Statistical Signal Processing Made Easy." In 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA). IEEE, 2015. http://dx.doi.org/10.1109/dicta.2015.7371250.

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Falie, Dragos, and Mihaela Ichim. "Generalized statistical operators for signal processing." In 2010 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2010. http://dx.doi.org/10.1109/ist.2010.5548510.

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Tewfik, A. H., and M. J. Kim. "Fast multiscale statistical signal processing algorithms." In [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1992. http://dx.doi.org/10.1109/icassp.1992.226358.

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Therrien, C. W. "Issues in multirate statistical signal processing." In Conference Record. Thirty-Fifth Asilomar Conference on Signals, Systems and Computers. IEEE, 2001. http://dx.doi.org/10.1109/acssc.2001.986988.

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Biswas, Sharmila, and Sandeep Singh Solanki. "SINGER IDENTIFICATION USING STATISTICAL SIGNAL PROCESSING." In ETHICS AND INFORMATION TECHNOLOGY. VOLKSON PRESS, 2020. http://dx.doi.org/10.26480/etit.02.2020.84.89.

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Saul, Lawrence K., Fei Sha, and Daniel D. Lee. "Statistical signal processing with nonnegativity constraints." In 8th European Conference on Speech Communication and Technology (Eurospeech 2003). ISCA: ISCA, 2003. http://dx.doi.org/10.21437/eurospeech.2003-343.

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Ji, Wu, CK Chan, JW Loh, FH Choo, and LH Chen. "Solar radiation prediction using statistical approaches." In Signal Processing (ICICS). IEEE, 2009. http://dx.doi.org/10.1109/icics.2009.5397540.

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Reports on the topic "Statistical Signal Processing"

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Kassam, Saleem A. Statistical Techniques for Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, December 1986. http://dx.doi.org/10.21236/ada185774.

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Kassam, Saleem A. Statistical Techniques for Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada262731.

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Kassam, S. A. Statistical Techniques for Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, May 1985. http://dx.doi.org/10.21236/ada167164.

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Amin, Moeness G. The 10th IEEE Signal Processing Workshop on Statistical Signal and Array Processing. Fort Belvoir, VA: Defense Technical Information Center, October 2000. http://dx.doi.org/10.21236/ada383267.

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Collins, Leslie M. Statistical Signal Processing for Demining: Experimental Validation. Fort Belvoir, VA: Defense Technical Information Center, June 1999. http://dx.doi.org/10.21236/ada370676.

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Collins, Leslie, Peter Torrione, Stacy Tantum, and Chris Ratto. Statistical Signal Processing Research for Landmine Detection. Fort Belvoir, VA: Defense Technical Information Center, March 2012. http://dx.doi.org/10.21236/ada572245.

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Kassam, Saleem A. Research on Statistical Techniques for Signal Processing. Fort Belvoir, VA: Defense Technical Information Center, February 1990. http://dx.doi.org/10.21236/ada218811.

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Baraniuk, Richard G. Multiscale Statistical Models for Signal and Image Processing. Fort Belvoir, VA: Defense Technical Information Center, June 2004. http://dx.doi.org/10.21236/ada425177.

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Collins, Leslie M. Statistical Signal Processing for Demining: Modeling and Experimental Validation. Fort Belvoir, VA: Defense Technical Information Center, December 2000. http://dx.doi.org/10.21236/ada394353.

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Collins, Leslie M., and Peter A. Torrione. Statistical Signal Processing for Demining: Continuation and Field Evaluation. Fort Belvoir, VA: Defense Technical Information Center, December 2008. http://dx.doi.org/10.21236/ada498587.

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Journal articles Dissertations / Theses Books
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