Results 211 to 220 of about 190,237 (262)
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1997 IEEE Ultrasonics Symposium Proceedings. An International Symposium (Cat. No.97CH36118), 2002
We describe a novel modular learning strategy for detection of a target signal of interest in a nonstationary environment, which is motivated by the information preservation rule. The strategy makes no assumptions on the environment. It incorporates three functional blocks: time-frequency analysis, feature extractions, and pattern classification, the ...
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We describe a novel modular learning strategy for detection of a target signal of interest in a nonstationary environment, which is motivated by the information preservation rule. The strategy makes no assumptions on the environment. It incorporates three functional blocks: time-frequency analysis, feature extractions, and pattern classification, the ...
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Acoustooptic Adaptive Signal Processing
SPIE Proceedings, 1986Acoustooptic methods for adaptive filtering of temporal signals are discussed. Two specific architectures are presented: one utilizing space-integration alone and the other combining both time and space integrating techniques. Performance issues regarding the space-integrating system are discussed in detail, and a description and experimental results ...
John Hong, Demetri Psaltis
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Adaptive signal processing through stochastic approximation
1970 IEEE Symposium on Adaptive Processes (9th) Decision and Control, 1970AbstractOne of the problems in signal processing is estimating the impulse response function of an unknown system. The well‐known Wiener filter theory has been a powerful method in attacking this problem. In comparison, the use of stochastic approximation method as an adaptive signal processor is relatively new.
R. J. WANG, S. TREITEL
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Environmentallly adaptive signal processing
The Journal of the Acoustical Society of America, 1997To achieve required system performance under difficult propagation and reverbaration conditions, signal processing systems must be environmentally adaptive. This paper uses results from statistical signal processing and wavelet transform theory to develop an estimator-correlator (EC) approach to environmental adaptivity.
Leon H. Sibul, Teresa L. Dixon
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2015
Adaptive frequency band (AFB) and ultra-wideband (UWB) systems require either rapidly changing or very high sampling rates. Conventional analog-to-digital devices are nonadaptive and have limited dynamic range. We investigate AFB and UWB sampling via a basis projection method.
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Adaptive frequency band (AFB) and ultra-wideband (UWB) systems require either rapidly changing or very high sampling rates. Conventional analog-to-digital devices are nonadaptive and have limited dynamic range. We investigate AFB and UWB sampling via a basis projection method.
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Algorithmic engineering in adaptive signal processing
IEE Proceedings F Radar and Signal Processing, 1992Algorithmic engineering provides a rigorous framework for describing and manipulating the type of building blocks commonly used to define parallel algorithms and architectures for digital signal processing. The concept is first illustrated by means of some fairly simple worked examples.
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An Adaptive Signal-Processing Approach to Online Adaptive Tutoring
2011Conventional intelligent or adaptive tutoring online systems rely on domain-specific models of learner behavior based on rules, deep domain knowledge, and other resource-intensive methods. We have developed and studied a domain-independent methodology of adaptive tutoring based on domain-independent signal-processing approaches that obviate the need ...
Bryan, Bergeron, Andrew, Cline
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Adaptive Systems for Signal Process
2000The chapter describes an important class of the nonlinear adaptive system commonly known as artificial neural networks or just simply neural networks. A neural network is a massively parallel distributed processor that has a natural propensity for storing experiential knowledge and making it available for use.
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Adaptive Signal Processing Applied in Telecommunications
IFAC Proceedings Volumes, 1992Abstract This paper overviews the applications of the adaptive signal processing in the evolving telecommunication network. The overview is divided into 3 segments, i.e. speech band adaptive systems, video band adaptive systems, and intelligent adaptive systems.
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Adaptive techniques of signal processing
2017 IEEE VI Forum Strategic Partnership of Universities and Enterprises of Hi-Tech Branches (Science. Education. Innovations) (SPUE), 2017The paper discusses adaptive techniques of signal processing. We consider empirical mode decomposition for signal processing as a modern adaptive technique and alternative to the wavelet transform. We describe the main tasks of signal processing handled by empirical mode decomposition.
Dmitry M. Klionskiy +2 more
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