Design of a Time Delay Reservoir Using Stochastic Logic: A Feasibility Study
This is an incremental study that addresses improving reservoir computing designs for specific applications, potentially benefiting researchers in neuromorphic or low-power computing.
The paper tackled designing a time delay reservoir using stochastic logic and introduced a re-seeding method to mitigate noise effects, achieving good performance on noise-tolerant classification benchmarks but noting limitations for regression tasks.
This paper presents a stochastic logic time delay reservoir design. The reservoir is analyzed using a number of metrics, such as kernel quality, generalization rank, 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.