Title
A new algorithm for the design of linear prediction error filtersusing cumulant-based MSE criteria
Abstract
Proposes a new algorithm for the design of (minimum-phase) linear prediction error (LPE) filters using two new cumulant (higher order statistics) based MSE criteria when the given stationary random signal x(n) is nonGaussian and contaminated by Gaussian noise. It is shown that the designed LPE filters based on the proposed criteria are identical to the conventional correlation (second-order statistics) based LPE filter as if x(n) were noise-free measurements. As correlation-based LPE filters, coefficients of the designed cumulant-based LPE filters can be obtained by solving a set of symmetric Toeplitz linear equations using the well-known computationally efficient Levinson-Durbin recursion. Moreover, the proposed two criteria are applicable for any cumulant order M⩾3, and one of the proposed criteria for M=3 reduces to Delopoulos and Giannakis' (1992) third-order cumulant-based MSE criterion. Some simulation results are then provided to support the analytical results
Year
DOI
Venue
1994
10.1109/78.324760
IEEE Transactions on Signal Processing
Keywords
Field
DocType
MSE criterion,cumulant order,new cumulant,symmetric Toeplitz linear equation,linear prediction error,higher order statistic,new algorithm,correlation-based LPE filter,LPE filter,proposed criterion,cumulant-based MSE criterion
Signal processing,Linear equation,Mathematical optimization,Digital filter,Higher-order statistics,Algorithm,Stochastic process,Linear prediction,Toeplitz matrix,Gaussian noise,Mathematics
Journal
Volume
Issue
ISSN
42
10
1053-587X
Citations 
PageRank 
References 
3
0.46
3
Authors
3
Name
Order
Citations
PageRank
Chong-Yung Chi11319102.57
Wen-Jie Chang230.46
Chih-Chun Feng3704.99