Liquid State Machine With Dendritically Enhanced Readout for Low-Power, Neuromorphic VLSI Implementations

@article{Roy2014LiquidSM,
  title={Liquid State Machine With Dendritically Enhanced Readout for Low-Power, Neuromorphic VLSI Implementations},
  author={Subhrajit Roy and Amitava Banerjee and Arindam Basu},
  journal={IEEE Transactions on Biomedical Circuits and Systems},
  year={2014},
  volume={8},
  pages={681-695}
}
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. Inspired by the… CONTINUE READING
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