Abstract
We investigated the performance of a blind source separation (BSS) system based on stochastic computing in the case of an aperiodic source signal by both simulation and a field programmable gate array (FPGA) experiment. We confirmed that our BSS system can successfully infer source signals from mixed signals. We show that the system succeeds in separating source signals from mixed signals after about 3.7 seconds at a clock frequency of 32 MHz on an FPGA.
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Hori, M., Ueda, M. (2009). Blind Source Separation System Using Stochastic Arithmetic on FPGA. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03040-6_103
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DOI: https://doi.org/10.1007/978-3-642-03040-6_103
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03039-0
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