TY - CHAP A1 - Bin Gao A2 - W.L. Woo ED1 - Ganesh R Naik Y1 - 2012-10-10 PY - 2012 T1 - Non-Negative Matrix Factorization with Sparsity Learning for Single Channel Audio Source Separation N2 - Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, Blind Source Separation (BSS) by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, image processing, telecommunications, medical signal processing and several data mining issues. This book brings the state-of-the-art of some of the most important current research of ICA related to Audio and Biomedical signal processing applications. The book is partly a textbook and partly a monograph. It is a textbook because it gives a detailed introduction to ICA applications. It is simultaneously a monograph because it presents several new results, concepts and further developments, which are brought together and published in the book. BT - Independent Component Analysis for Audio and Biosignal Applications SP - Ch. 5 UR - https://doi.org/10.5772/48068 DO - 10.5772/48068 SN - PB - IntechOpen CY - Rijeka Y2 - 2021-05-13 ER -