Optimizing eigenvalues of the adjacency matrix in linear reservoir computers yields better training and test performance than random linear reservoirs and often beats comparable nonlinear ones.
Shuhei Sugiura, Ryo Ariizumi, Toru Asai, and Shun-Ichi Azuma
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Optimizing the Network Topology of a Linear Reservoir Computer
Optimizing eigenvalues of the adjacency matrix in linear reservoir computers yields better training and test performance than random linear reservoirs and often beats comparable nonlinear ones.