Hirschman optimal transform block LMS adaptive filter

被引：0
|
作者：
Alkhouli, Osaina [1 ]
DeBrunner, Victor E. [2 ]
机构：
[1] Univ Oklahoma, Sch Elect & Comp Engn, Norman, OK 73019 USA
[2] Florida State Univ, Dept Elect & Comp Engn, Tallahassee, FL 32306 USA
来源：
2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL III, PTS 1-3, PROCEEDINGS | 2007年
关键词：
adaptive filters; fast Fourier transforms; entropy;
D O I：
暂无
中图分类号：
O42 [声学];
学科分类号：
070206 ; 082403 ;
摘要：
In this paper, we derive a "convolution theorem" suitable for the Hirschman optimal transform (HOT), a unitary transform derived from a discrete-time, discrete-frequency version of the entropy-based uncertainty measure first described by Hirschman [10]. We use the result to develop a fast block-LMS adaptive filter which we call the HOT Block-LMS adaptive filter. This filter requires slightly less than half of the computations that are required for the FFT Block-LMS adaptive filter. The simulations show that the convergence rates of both the HOT and FFT Block-LMS adaptive filters are similar.
引用
收藏
页码：1305 / +
页数：2
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