Blind Separation of Monaural Signals using Complex Wavelets
In this paper, a new method of blind source separation of monaural signals is presented. It is based on similarity criteria between envelopes and frequency trajectories of the components of the signal, and on its onset and offset times. The main difference with previous works is that in this paper, the input signal has been filtered using a flexible complex band pass filter bank that is a discrete version of the Complex Continuous Wavelet Transform (CCWT). Our main purpose is to show that the CCWT can be a powerful tool in blind separation, due to its strong coherence in both time and frequency domains. The presented separation algorithm is a first approximation to this important task. An example set of four synthetically mixed monaural signals have been analyzed by this method. The obtained results are promising.