Liquid State Machine with Dendritically Enhanced Readout for Low-power, Neuromorphic VLSI Implementations

20 Nov 2014 Subhrajit Roy Amitava Banerjee Arindam Basu

In this paper, we describe a new neuro-inspired, hardware-friendly readout stage for the liquid state machine (LSM), a popular model for reservoir computing. Compared to the parallel perceptron architecture trained by the p-delta algorithm, which is the state of the art in terms of performance of readout stages, our readout architecture and learning algorithm can attain better performance with significantly less synaptic resources making it attractive for VLSI implementation... (read more)

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