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1 November 1990 Nonlinear classification and adaptive structures
Colin F. N. Cowan, Peter M. Grant, Shang-Liang Chen, Gavin J. Gibson
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Proceedings Volume 1348, Advanced Signal Processing Algorithms, Architectures, and Implementations; (1990) https://doi.org/10.1117/12.23465
Event: 34th Annual International Technical Symposium on Optical and Optoelectronic Applied Science and Engineering, 1990, San Diego, CA, United States
Abstract
The main purpose of this paper is to examine a number of possible architectures for nonlinear adaptive filtering specifically related to adaptive equalisation. The approach taken proceeds by first reformulating the filtering process as a form of classification task in N dimensions. In the case of filtering the dimensionality is determined by the number of data samples in the filter data input vector. The task of classification then proceeds using a number of possible strategies i. e. the multilayer perceptron Volterra series modeling and cluster analysis. The techniques are evaluated in comparison with normal linear equalisation procedures.
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Colin F. N. Cowan, Peter M. Grant, Shang-Liang Chen, and Gavin J. Gibson "Nonlinear classification and adaptive structures", Proc. SPIE 1348, Advanced Signal Processing Algorithms, Architectures, and Implementations, (1 November 1990); https://doi.org/10.1117/12.23465
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KEYWORDS
Nonlinear filtering
Digital filtering
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