Identifiability Conditions for Compressive Multichannel Blind Deconvolution

Identifiability Conditions for Blind and Semi-blind Multiuser Multichannel Identification

We explore the identifiability conditions for blind and semi-blind multiuser multichannel identification. Starting with the deterministic approach, we compare the identifiability conditions on the channel and the sources of training sequence based channel identification, blind and semi-blind channel identification. Further on, we use the stochastic approach with Gaussian priors for the source s...

Modified Sparse Multichannel Blind Deconvolution

Super-exponential methods for multichannel blind deconvolution

Multichannel blind deconvolution has received increasing attention during the last decade. Recently, Martone [3, 4] extended the super-exponential method proposed by Shalvi and Weinstein [1, 2] for single-channel blind deconvolution to multichannel blind deconvolution. However, the Martone extension suffers from two type of serious drawbacks. The objective of this paper is to obviate these draw...

Two-stage Approach for Multichannel Blind Deconvolution

Multichannel blind deconvolution is a method that allows the separation of sources from which only convolutive mixtures are observable. It is an attractive technique for separating independent speech and noise signals. Fast tracking is essential in order to cope with real nonstationary environments. Based on the principle of information maximization, a new two-stage algorithm is proposed which ...

Dynamic Programming for Multichannel Blind Seismic Deconvolution

We present an algorithm for multichannel blind deconvolution of seismic signals, which exploits lateral continuity of earth layers by dynamic programming approach. We assume that reflectors in consecutive channels, related to distinct layers, form continuous paths across channels. We introduce a quality measure for evaluating the quality of a continuous path, and iteratively apply dynamic progr...