Analysis of time series classification of a multi-layer reservoir neural network based on asynchronous cellular automaton neurons with transmission delays

In this paper, a novel multi-layer reservoir neural network with axonal delays is proposed using an asynchronous cellular automaton neuron model. A learning method of the network based on the simulated annealing is also proposed. Then, performance of time series classification of the network is analyzed with respect to parameters of the reservoir layers. Based on the analysis results, a design method of the network to realize higher performance of the time series classification is proposed. Furthermore, the proposed network is implemented as a hardware description language code (Verilog-HDL code) and post-synthesize simulations validate its classification function.