Download Source separation for microphone arrays using multichannel conjugate gradient techniques This paper proposes a new scheme to improve the source separation problem aimed to microphone array applications like WFS based teleconference systems. A multichannel, sub-band approach to reduce computational complexity is presented. Also, instead of using the LMS adaptive algorithm, a new system based on hybrid Conjugate Gradient-nLMS techniques is developed to accelerate the convergence time. This adaptive algorithm is controlled by a voice activity detector block that basically detects double talk situations and freezes the adaptation process to avoid the appearance of sound artifacts which may cause a significant degradation of the recovered signals and have a great impact in the quality of the full system.
Download Conjugate gradient techniques for multichannel acoustic echo cancellation Conjugate Gradient (CG) techniques are suitable for resolution of time-variant system identification problems: adaptive equalization, echo cancellation, active noise cancellation, linear prediction, etc. These systems can be seen as optimization problems and CG techniques can be used to solve them. It has been demonstrated that, in the single-channel case, the conjugate gradient techniques provide a similar solution in terms of convergence rate than those provided by the recursive least square (RLS) method, involving higher complexity than the least mean square (LMS) but lower than RLS without stability issues. The advantages of these techniques are especially valuable in the case of high complexity and magnitude problems like multi-channel systems. This work develops CG algorithm for the adaptive MIMO (multiple-input and multiple-output) systems and tests it by solving a multichannel acoustic echo cancellation (MAEC) problem.