Gradient Flow Independent Component Analysis in Micropower VLSI

Part of Advances in Neural Information Processing Systems 18 (NIPS 2005)

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Authors

Abdullah Celik, Milutin Stanacevic, Gert Cauwenberghs

Abstract

We present micropower mixed-signal VLSI hardware for real-time blind separation and localization of acoustic sources. Gradient flow representation of the traveling wave signals acquired over a miniature (1cm diameter) array of four microphones yields linearly mixed instantaneous observations of the time-differentiated sources, separated and localized by independent component analysis (ICA). The gradient flow and ICA processors each measure 3mm 3mm in 0.5 m CMOS, and consume 54 W and 180 W power, respectively, from a 3 V supply at 16 ks/s sampling rate. Experiments demonstrate perceptually clear (12dB) separation and precise localization of two speech sources presented through speakers positioned at 1.5m from the array on a conference room table. Analysis of the multipath residuals shows that they are spectrally diffuse, and void of the direct path.