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A Neural Architecture Search based Framework for Liquid State Machine Design
By exploring the design space in network architectures and parameters, recent works have demonstrated great potential for improving the accuracy of LSM model with low complexity.
Exploration of Input Patterns for Enhancing the Performance of Liquid State Machines
To mitigate the difficulty in effectively dealing with huge input spaces of LSM, and to find that whether input reduction can enhance LSM performance, we explore several input patterns, namely fullscale, scanline, chessboard, and patch.
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