Computationally efficient algorithm for adaptive quadratic Volterra filters

Xiaohui Li, William Kenneth Jenkins, Charles W. Therrien

    Research output: Contribution to journalConference article

    3 Scopus citations

    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 languageEnglish (US)
    Pages (from-to)2184-2187
    Number of pages4
    JournalProceedings - IEEE International Symposium on Circuits and Systems
    Volume4
    Publication statusPublished - Jan 1 1997
    EventProceedings of the 1997 IEEE International Symposium on Circuits and Systems, ISCAS'97. Part 4 (of 4) - Hong Kong, Hong Kong
    Duration: Jun 9 1997Jun 12 1997

      Fingerprint

    All Science Journal Classification (ASJC) codes

    • Electrical and Electronic Engineering

    Cite this