Abstract
The structure of the input autocorrelation matrix in Volterra second order adaptive filters for general colored Gaussian input processes is analyzed to determine how to best formulate a computationally efficient fast adaptive algorithm. It is shown that when the input signal samples are ordered properly within the input data vector, the autocorrelation matrix of quadratic filter inherits a block diagonal structure, with some of the sub-blocks also having diagonal structure. Some new results in developing and evaluating computationally efficient quasi-Newton adaptive algorithms are presented that take advantage of the sparsity and unique structure of the correlation matrix that results from this formulation.
Original language | English (US) |
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Pages (from-to) | 2184-2187 |
Number of pages | 4 |
Journal | Proceedings - IEEE International Symposium on Circuits and Systems |
Volume | 4 |
State | Published - Jan 1 1997 |
Event | Proceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4) - Hong Kong, Hong Kong Duration: Jun 9 1997 → Jun 12 1997 |
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering