DocumentCode :
284743
Title :
A family of quantization based piecewise linear filter networks
Author :
Sorensen, John Aasted
Author_Institution :
Electron. Inst., Tech. Univ. of Denmark, Lyngby, Denmark
Volume :
2
fYear :
1992
fDate :
23-26 Mar 1992
Firstpage :
329
Abstract :
A family of quantization-based piecewise linear filter networks is proposed. For stationary signals, a filter network from this family is a generalization of the classical Wiener filter with an input signal and a desired response. The construction of the filter network is based on quantization of the input signal x(n) into quantization classes. With each quantization class is associated a linear filter. The filtering at time n is carried out by the filter belonging to the actual quantization class of x(n ) and the filters belonging to the neighbor quantization classes of x(n) (regularization). This construction leads to a three-layer filter network. The first layer consists of the quantization class filters for the input signal. The second layer carries out the regularization between neighbor quantization classes, and the third layer constitutes a decision of quantization class from where the resulting output is obtained
Keywords :
analogue-digital conversion; filtering and prediction theory; feedforward neural nets; quantization based piecewise linear filter networks; stationary signals; three-layer filter network; Approximation error; Ear; Filtering algorithms; Nonlinear filters; Piecewise linear approximation; Piecewise linear techniques; Quantization; Wiener filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location :
San Francisco, CA
ISSN :
1520-6149
Print_ISBN :
0-7803-0532-9
Type :
conf
DOI :
10.1109/ICASSP.1992.226053
Filename :
226053
Link To Document :
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