S Van Gerven

Signal separation in a symmetric adaptive noise canceler by output decorrelation

An algorithm for adaptive noise cancellation and signal separation is presented. It is an extension of the classical Widrow least-mean-square (LMS) noise canceler for the case of signal leakage into the noise reference. The algorithm is derived intuitively from the interpolation of the adaptive noise canceler as a decorrelator between signal estimate and noise in which the noise reference is replaced by a signal-free noise estimate. Thus, a symmetric adaptive decorrelator is obtained for signal separation, as the artificial distinction between signal and noise concepts has disappeared. The algorithm has its limitations as convergence to the desired solution and stability around it can only be guaranteed for a subclass of signal separation problems. These restrictions are rarely violated in real life problems, however, and seem to be fundamental to the signal separation problem rather than algorithm dependent.<<ETX>>

On the use of decorrelation in scalar signal separation

In this paper we describe a method to separate a scalar mixture of two signals. The method is based on the use of decorrelation as a signal separation criterion. It is proven analytically that decorrelating the output signals at different time lags is sufficient provided that the normalised autocorrelation functions of the source signals are sufficiently distinct. The method involves an iterative least-squares solution of a set of nonlinear equations. Alternatively, a gradient search algorithm can also be used to find the minimum of the sum of squares of these equations. Both time- and frequency-domain formulations are given. Some convergence and stability issues are discussed and a small example is given at the end.<<ETX>>

Multiple beam broadband beamforming: filter design and real-time implementation

In this paper the design and implementation of a truly broadband beamformer is described. Using only a limited number of microphones a beamformer has been developed with a reasonably homogeneous beampattern over the entire speech bandwidth. The solution is obtained as the result of a filter-and-sum operation. Beams are steered towards different listening-directions and for each direction a set of spatio-temporal filters had to be designed. All beams operate in parallel and a beam-selection procedure picks out the beam with the most prominent speech signal. The complete system has been implemented in real-time using 1 MOTOROLA-56001 and 4 TMS-320C40 processors.