A NEURAL-NET ALGORITHM FOR MULTIDIMENSIONAL MINIMUM RELATIVE-ENTROPY SPECTRAL-ANALYSIS

被引:0
|
作者
ZHUANG, XH [1 ]
HUANG, Y [1 ]
YU, FA [1 ]
ZHANG, P [1 ]
机构
[1] UNIV WASHINGTON,DEPT ELECT ENGN,SEATTLE,WA 98195
基金
美国国家科学基金会;
关键词
D O I
10.1109/78.275638
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
A neural net algorithm is presented to solve the general 1-D or multidimensional minimum relative-entropy spectral analysis. The problem is formulated as a primal constrained optimization and is reduced to solving an initial value problem of differential equation of Lyapunov type. The initial value problem of Lyapunov system comprises the basis of our neural net algorithm. Experiments with simulated data convincingly showed that the algorithm did provide the multidimensional minimum relative-entropy spectral estimator with the autocorrelation matching property with computational efficiency.
引用
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页码:489 / 491
页数:3
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