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Reservoir computing demonstrates nonlinear dynamics and memory in neuromorphic systems, suggesting an efficient approach for hardware applications.
Reservoir computing (RC) provides a training efficient alternative to recurrent neural networks by fixing recurrent weights and training only a linear readout. In hardware, physical reservoirs harness intrinsic device dynamics...
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Jeong et al. (2026) studied this question.
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