Source separation using single channel ICA
Signal Processing
Finite sample effects of the fast ICA algorithm
Neurocomputing
A histogram based data-reducing algorithm for the fixed-point independent component analysis
Pattern Recognition Letters
Glottal Source biometrical signature for voice pathology detection
Speech Communication
New algorithms for blind recognition of OFDM based systems
Signal Processing
A two-stage Independent Component Analysis-based method for blind detection in CDMA systems
Digital Signal Processing
| Hi-index | 754.84 |
A necessary and sufficient condition for blind deconvolution (without observing the input) of nonminimum-phase linear time-invariant systems (channels) is derived. Based on this condition, several optimization criteria are proposed, and their solution is shown to correspond to the desired response. These criteria involve the computation only of second- and fourth-order moments, implying a simple tap update procedure. The proposed methods are universal in the sense that they do not impose any restrictions on the probability distribution of the (unobserved) input sequence. It is shown that in several important cases (e.g. when the additive noise is Gaussian), the proposed criteria are essentially unaffected