Adaptive Blind Multichannel Identification

Abstract

Blind multichannel identification was first introduced in the mid 1970s and initially studied in the communication society with the intention of designing more-efficient communication systems by avoiding a training phase. Recently this idea has become increasingly interesting for acoustics and speech processing research, driven by the fact that in most acoustic applications for speech processing and communication very little or nothing is known about the source signals. Since human ears have an extremely wide dynamic range and are much more sensitive to weak tails of the acoustic impulse responses, these impulse responses need to be modeled using fairly long filters. Attempting to identify such a multichannel system blindly with a batch method involves intensive computational complexity. This is not just bad system design, but technically rather implausible, particularly for real-time systems. Therefore, adaptive blind multichannel identification algorithms are favorable and pragmatically useful. This chapter describes some fundamental issues in blind multichannel identification and reviews a number of state-of-the-art adaptive algorithms.