Blind identification and equalization of two-channel FIR systems in unbalanced noise environments
Signal Processing - Content-based image and video retrieval
Subspace methods for multimicrophone speech dereverberation
EURASIP Journal on Applied Signal Processing
Blind adaptive channel equalization with performance analysis
EURASIP Journal on Applied Signal Processing
Time delay estimation in room acoustic environments: an overview
EURASIP Journal on Applied Signal Processing
Dereverberation by using time-variant nature of speech production system
EURASIP Journal on Advances in Signal Processing
Integrated speech enhancement method using noise suppression and dereverberation
IEEE Transactions on Audio, Speech, and Language Processing
MCA: a multichannel approach to SAR autofocus
IEEE Transactions on Image Processing
Parallel image processing with the block data parallel architecture
IBM Journal of Research and Development
Image reconstruction from phased-array MRI data based on multichannel blind deconvolution
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Model-based feature enhancement for reverberant speech recognition
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
Speech dereverberation based on variance-normalized delayed linear prediction
IEEE Transactions on Audio, Speech, and Language Processing - Special issue on processing reverberant speech: methodologies and applications
Propagation of blood function errors to the estimates of kinetic parameters with dynamic PET
Journal of Biomedical Imaging - Special issue on modern mathematics in biomedical imaging
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
| Hi-index | 35.68 |
A new algorithm is proposed for the deconvolution of an unknown, possibly colored, Gaussian or nonstationary signal that is observed through two or more unknown channels described by rational system transfer functions. More specifically, not only the root (pole and zero) locations but also the orders of the channel transfer functions are unknown. It is assumed that the channel orders may be overestimated. The proposed algorithm estimates the orders and root locations of the channel transfer functions, therefore it can also be used in multichannel system identification problems. The input signal is allowed to be nonstationary and the channel transfer functions may be a nonminimum phase as well as noncausal, hence the proposed algorithm is particularly suitable for applications such as dereverberation of speech signals recorded through multiple microphones. Several experimental results indicate improvement compared to the existing methods in the literature