STUDIES OF OPTIMAL MEMORY FOR DISCRETE-TIME FIR FILTERS IN STATE-SPACE

被引：0

作者：

Ramirez-Echeverria, Felipe ^{[1
]}

Sarr, Amadou ^{[2
]}

Ibarra-Manzano, Oscar G. ^{[1
]}

Shmaliy, Yuriy S. ^{[1
]}

机构：

[1] Univ Guanajuato, Dept Elect, Salamanca, Mexico

[2] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4L8, Canada

来源：

2012 IEEE STATISTICAL SIGNAL PROCESSING WORKSHOP (SSP) | 2012年

关键词：

FIR filtering; optimal memory; unbiased Kalman-like filter; MODELS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We address two efficient estimators of optimal memory for FIR filters in discrete-time state-space via the conditional mean square error and real measurement. In the latter case, the algorithm does not involve neither a reference nor the noise covariances, but requires a learning circle. Although a justification has been provided for the Kalman-like unbiased FIR filter, the estimators can be used universally. Testing by the two-state polynomial model has shown a very good correspondence with the predicted values.

引用

页码：349 / 352

页数：4

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