Some theoretical issues on continuous process neural networks

Aim at the problems that the inputs and outputs of some practical nonlinear systems are Continuous time signals, we brought forward a Continuous process neuron and process neural networks model. The input and output of the defined process neuron are Continuous time functions, and the space-time aggregation operation can reflect the space aggregation of the input signals and the time cumulative effect in the process of input at the same time, and can also realize the nonlinear real-time mapping between the input and output. A Continuous feedforward process neural networks model is given in this paper, and the corresponding property theorems are also proved, including continuity, function approximation ability and computational capacity.EI0101838-18413