Fluctuation and Noise Letters Vol. 0, No. 0 (2001) 000—000 ❢ c World Scientific Publishing Company ADAPTIVE NOISE CANCELLATION FOR MULTI-SENSORY SIGNALS SERGIY A. VOROBYOV, ANDRZEJ CICHOCKI Laboratory for Advanced Brain Signal Processing, Brain Science Institute The Institute of Physical and Chemical Research (RIKEN) 2-1 Hirosawa, Wako-shi, Saitama 351-0198 JAPAN Email: {svor,cia}@bsp.brain.riken.go.jp YEVGENIY V. BODYANSKIY Control Systems Research Laboratory Kharkiv State Technical University of Radioelectronics 14 Lenin Ave., Kharkiv 61166 UKRAINE Email: bodya@kture.kharkov.ua Received (received date) Revised (revised date) Accepted (accepted date) This paper describes a fast adaptive algorithm for noise cancellation using multi-sensory signal recordings of the same noisy source. It is shown that the performance of the new procedure for noise cancellation for multi-sensory signals is improved when compared to previously proposed methods. A short overview of the previously proposed methods is given. Optimality of the algorithm is discussed and numerical simulation is included to show the validity and effectiveness of the algorithm. Keywords : Noise cancellation; Multi-sensory signal; Adaptive filtering; Optimization; Learning. 1. Introduction Noise cancellation is a special case of optimal filtering which can be applied when some information about the reference noise signal is available. The noise cancella- tion technique has many applications, e.g. speech processing, echo cancellation and enhancement, antenna array processing, biomedical signal and image processing and so on [1-4]. The standard methods of noise cancellation use only one primary signal [1]. However, in many applications, especially in biomedical signal processing, we are able to measure several primary signals. Often this possibility can help to improve the performance of noise cancellation procedure. The standard approach is to make use of several noisy signals, by recording from