Maximum likelihood estimation of amplitude-modulated time series

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• 作者：Ghogho ; Mounir ; Garel ; Bernard
• 关键词：Amplitude modulated time series ; Multiplicative noise ; Cramé ; r&ndash ; Rao bound ; Maximum likelihood estimation ; Abrupt change
• 刊名：Signal Processing
• 出版年：1999
• 出版时间：June, 1999
• 年：1999
• 卷：75
• 期：2
• 页码：99-116
• 全文大小：234 K

文摘

The concern of this paper is to study a class of nonstationary signals of the form x(t)c(t) where x(t) is a stationary Gaussian stochastic process and c(t) is a deterministic signal. The process x(t) is modeled by an autoregressive (AR) process. The deterministic signal c(t) is a known function of a finite-dimensional unknown vector. Closed-form expressions are derived for the finite-sample Cramér–Rao bound. Algorithms for the maximum likelihood estimation of c(t) and the spectral density of x(t) are developed. The proposed methods are applied to the problem of estimating abrupt change in multiplicative noise.