Liquid state machine with dendritically enhanced readout for low-power, neuromorphic VLSI implementations
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 re...
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Main Authors: | , , |
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Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2015
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/102407 http://hdl.handle.net/10220/24572 |
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Institution: | Nanyang Technological University |
Language: | English |