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An FPGA Implementation of a Time Delay Reservoir Using Stochastic Logic

Lisa Loomis,N. McDonald,Cory E. Merkel

Published 2018 in ACM Journal on Emerging Technologies in Computing Systems

ABSTRACT

This article presents and demonstrates a stochastic logic time delay reservoir design in FPGA hardware. The reservoir network approach is analyzed using a number of metrics, such as kernel quality, generalization rank, and performance on simple benchmarks and is also compared to a deterministic design. A novel re-seeding method is introduced to reduce the adverse effects of stochastic noise, which may also be implemented in other stochastic logic reservoir computing designs, such as echo state networks. Benchmark results indicate that the proposed design performs well on noise-tolerant classification problems, but more work needs to be done to improve the stochastic logic time delay reservoir's robustness for regression problems. In addition, we show that the stochastic design can significantly reduce area cost if the conversion between binary and stochastic representations is implemented efficiently.

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