By Topic

ASSP Magazine, IEEE

Issue 4 • Date Oct. 1989

Filter Results

  • Set membership identification in digital signal processing

    Page(s): 4 - 20
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1374 KB)  

    Set membership (SM) identification refers to a class of techniques for estimating parameters of linear systems or signal models under a priori information that constrains the solutions to certain sets. When data do not help refine these membership sets, the effort of updating the parameter estimates at those points can be avoided. An intuitive development is given, first in one dimension and then in the general case, of an SM algorithm based on least-squares estimation. Two useful versions of the method are described, one of which can be implemented on a systolic array processor. The relationship of the featured SM method to both historical and current developments is discussed. Application to real speech data illustrates the developments.<> View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

This Magazine ceased production in 1990. The current retitled publication is IEEE Signal Processing Magazine.

Full Aims & Scope