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Blind Channel Identification Based on Noisy Observation by Stochastic Approximation Method

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Abstract

A stochastic approximation algorithm for estimating multichannel coefficients is proposed, and the estimate is proved to converge to the true parameters a.s. up-to a constant scaling factor. The estimate is updated after receiving each new observation, so the output data need not be collected in advance. The input signal is allowed to be dependent and the observation is allowed to be corrupted by noise, but no noise statistics are used in the estimation algorithm.

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Fang, HT., Chen, HF. Blind Channel Identification Based on Noisy Observation by Stochastic Approximation Method. Journal of Global Optimization 27, 249–271 (2003). https://doi.org/10.1023/A:1024851425821

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