Conference paper
A family of quantization based piecewise linear filter networks
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
| Language: | English |
|---|---|
| Year: | 1992 |
| Pages: | 329-332 |
| Proceedings: | 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing |
| ISBN: | 0780305329 and 9780780305328 |
| ISSN: | 2379190x and 15206149 |
| Types: | Conference paper |
| DOI: | 10.1109/ICASSP.1992.226053 |
| ORCIDs: | Sørensen, John Aasted |
Approximation error Ear Filtering algorithms Nonlinear filters Piecewise linear approximation Piecewise linear techniques Quantization Wiener filter analogue-digital conversion feedforward neural nets filtering and prediction theory quantization based piecewise linear filter networks stationary signals three-layer filter network
