NEW CUMULANT-BASED APPROACHES FOR NON-GAUSSIAN TIME-VARYING AR MODELS

被引：9

作者：

BAKRIM, M

ABOUTAJDINE, D

NAJIM, M

机构：

[1] Leesa, BP 1014, Faculté des Sciences de Rabat, Rabat, Maroc

[2] Equipe Signal et Image, ENSERB, F-33405 Talence Cedex

来源：

SIGNAL PROCESSING | 1994年 / 39卷 / 1-2期

关键词：

NONSTATIONARY NON-GAUSSIAN SIGNALS; CAUSAL AUTOREGRESSIVE EVOLUTION MODELS; AUTOCORRELATION; CUMULANTS; BATCH-TYPE EVOLUTIVE METHOD; ADAPTIVE GRADIENT-TYPE METHOD; COMPARATIVE STUDY;

D O I：

10.1016/0165-1684(94)90127-9

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：

In this paper, we present two new cumulant-based methods for time-varying AR parameters estimation: a batch-type evolutive method and an adaptive gradient-type algorithm. The evaluation of these techniques is performed through simulations on synthetic non-Gaussian signals contaminated by an additive, zero-mean, white Gaussian noise. We compare them to their autocorrelation-based counterparts. The obtained results show, using an appropriate criterion, the superiority of our cumulant-based evolutive method over both its autocorrelation-based version and the proposed cumulant-based gradient-type algorithm at the expense of more computational complexity.

引用

页码：107 / 115

页数：9

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