Doctoral Dissertations

Author

Jianming Liu

Keywords and Phrases

Adaptive filter; Echo cancellation; Sparse system identification

Abstract

"Sparse system identification has attracted much attention in the field of adaptive algorithms, and the adaptive filters for sparse system identification are studied. Firstly, a new family of proportionate normalized least mean square (PNLMS) adaptive algorithms that improve the performance of identifying block-sparse systems is proposed. The main proposed algorithm, called block-sparse PNLMS (BS-PNLMS), is based on the optimization of a mixed ℓ2,1 norm of the adaptive filter's coefficients. A block-sparse improved PNLMS (BS-IPNLMS) is also derived for both sparse and dispersive impulse responses. Meanwhile, the proposed block-sparse proportionate idea has been extended to both the proportionate affine projection algorithm (PAPA) and the proportionate affine projection sign algorithm (PAPSA).

Secondly, a generalized scheme for a family of proportionate algorithms is also presented based on convex optimization. Then a novel low-complexity reweighted PAPA is derived from this generalized scheme which could achieve both better performance and lower complexity than previous ones. The sparseness of the channel is taken into account to improve the performance for dispersive system identification. Meanwhile, the memory of the filter's coefficients is combined with row action projections (RAP) to significantly reduce the computational complexity.

Finally, two variable step-size zero-point attracting projection (VSS-ZAP) algorithms for sparse system identification are proposed. The proposed VSS-ZAPs are based on the approximations of the difference between the sparseness measure of current filter coefficients and the real channel, which could gain lower steady-state misalignment and also track the change in the sparse system"--Abstract, page iv.

Advisor(s)

Grant, Steven L.

Committee Member(s)

Beetner, Daryl G.
Kosbar, Kurt Louis
Moss, Randy Hays, 1953-
Insall, Matt

Department(s)

Electrical and Computer Engineering

Degree Name

Ph. D. in Electrical Engineering

Publisher

Missouri University of Science and Technology

Publication Date

Spring 2016

Journal article titles appearing in thesis/dissertation

  • Proportionate adaptive filtering for block-sparse system identification
  • Proportionate affine projection algorithms for block-sparse system identification
  • Block sparse memory improved proportionate affine projection sign algorithm
  • A low complexity reweighted proportionate affine projection algorithm with memory and row action projection
  • A new variable step-size zero-point attracting projection algorithm
  • An improved variable step-size zero-point attracting projection algorithm

Pagination

xii, 119 pages

Note about bibliography

Includes bibliographic references.

Rights

© 2016 Jianming Liu, All rights reserved.

Document Type

Dissertation - Open Access

File Type

text

Language

English

Library of Congress Subject Headings

Adaptive filters
Sparse matrices -- Data processing
System identification
Echo suppression (Telecommunication) -- Computer simulation

Thesis Number

T 10919

Electronic OCLC #

952595903

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