Abstract: Owing to the parallelism feature and convenient hardware implementation of recurrent neural network (RNN), many RNN models have been proposed to solve linear and nonlinear algebra problems.
Abstract: This work extends a matrix-based numerical methodology to cover fully canonical generalized Chevyshev (GC) transfer functions by reconfiguring canonical filter topologies into dangling ...
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