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Showing 1 to 3 of 3 for “"Liquid State Machines"”.
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Improving Liquid State Machines Through Iterative Refinement of the Reservoir
<p>Liquid State Machines (LSMs) exploit the power of recurrent spiking neural networks (SNNs) without training the SNN. Instead, a reservoir, or liquid, is randomly created which acts as a filter for a readout function. We develop three methods for iteratively refining a randomly generated liquid …
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Optimizing Reservoir Computing Architecture for Dynamic Spectrum Sensing Applications
… high Signal-to-Noise Ratio (SNR). Leveraging Liquid State Machines (LSMs), which emulate spiking neural networks like the ones in the human brain, prove to be highly effective for real-time data monitoring for such temporal tasks. The inherent advantages of LSM-based recurrent neural networks, …
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Energy Efficient Deep Spiking Recurrent Neural Networks: A Reservoir Computing-Based Approach
… different categories of RC systems, namely, echo state networks (ESNs), liquid state machines (LSMs), and delayed feedback reservoirs (DFRs). In this dissertation a novel structure of RNNs which is inspired by dynamic delayed feedback loops is introduced. In the reservoir (recurrent) layer of DFR, …