Blind separation and deconvolution of MIMO-FIR system with colored sound inputs using SIMO-model-based ICA
- Resource Type
- Conference
- Authors
- Saruwatari, H.; Yamajo, H.; Takatani, T.; Nishikawa, T.; Shikano, K.
- Source
- IEEE Workshop on Statistical Signal Processing, 2003 Statistical signal processing Statistical Signal Processing, 2003 IEEE Workshop on. :438-441 2003
- Subject
- Signal Processing and Analysis
General Topics for Engineers
Deconvolution
Independent component analysis
Speech
Filters
Signal processing
Microphones
Information science
Electronic mail
Filtering algorithms
MIMO
- Language
We propose a new two-stage blind separation and deconvolution algorithm for multiple-input multiple-output (MIMO)-FIR system driven by colored sound sources, in which a new single-input multiple-output (SIMO)-model-based ICA (SIMO-ICA) and blind multichannel inverse filtering are combined. SIMO-ICA can separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources. After SIMO-ICA, a simple blind deconvolution technique for the SIMO model can be applied even when each source signal is temporally correlated. The simulation results reveal that the proposed algorithm can successfully achieve the separation and deconvolution for a convolutive mixture of speech.