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Abstract: The paper presents a maximum likelihood (ML) blind channel equalisation algorithm based on the expectation-maximisation (EM) algorithm.
ABSTRACT. The paper presents a maximum likelihood (ML) blind channel equalisation algorithm based on the expectation- maximisation (EM) algorithm.
The availability of multi- channel outputs for the same channel input improves the reliability of the estimates. A reduced-cost blind equalisation algorithm ...
Fractionally-spaced blind channel equalisation using hidden Markov models ... model for fractionally-spaced channel equalisation. is obtained from the ...
We present a maximum likelihood (ML) blind identification algorithm for fractionally spaced communication channels. The algorithm is based on the ...
Oct 22, 2024 · PDF | We consider the problem of blind estimation of a communication channel based on the oversampled channel output.
Fractionally-spaced blind channel equalisation using hidden Markov models. Authors: Vikram Krishnamurthy, University of Melbourne (Australia) Kutluyl ...
We focus on one particular, commonly used, blind equalization method, considering an adaptive linear feedforward equalizer with tap weights updated by the ...
Missing: equalisation | Show results with:equalisation
Based on a more general structure for multi-input–multi-output channels, we present a method using fractional sampling and BSS to recover transmitted symbols in ...
The HMM estimator yields optimal filtered estimates of the Markov state and parameters of a Markov chain in white noise. The state estimator is based on the.