Time Domain Characteristic Analysis of Non-coupled PCNN

The Pulse-Coupled Neural Network (PCNN) model is a multi-parameter neural network, the input-output characteristics are greatly affected by parameters setting. The traditional non-coupled PCNN model, which only uses the gray value as input, results in a certain inhibition of the network's pulse firing characteristics. In this paper, based on the traditional non-coupled PCNN model, from the perspective of system equations, the firing characteristics of the non-simplified uncoupled PCNN model with coupled linking term is studied, and the mathematical expressions for firing time and interval were summarized. By constructing different neighborhood linking weight matrix patterns, the impact of the linking weight matrix and coefficients on network characteristics was analyzed, and the constraint conditions for parameters a E , V E , and V F were provided. Finally, through experiments simulation, the correctness of the theoretical analysis is verified, providing theoretical support for researching on fully parameterized PCNN and the application of the studied model in image processing.