Research On PCNN Chaotic Features And Hardware Implementation

Pulse Coupled Neural Network (PCNN) is a new kind of neural network. It was proposed according to the phenomenon of synchronization of impulses which was derived from the observation on the visual cortical neurons of cats, and its feature that similar neurons fire (generate pulses) synchronously is closer to the biological visual characteristic, so the applications of PCNN have caused extensive attention. As a kind of nonlinear dynamic system, PCNN has the chaotic characteristic, but there are few literatures about it. Most of current literatures pay close attention to the research into the simulation of PCNN model, and the PCNN algorithm implementation based on hardware platforms is still a developing hotspot and is becoming a focus of research.This dissertation focuses on the research into the chaotic characteristic of PCNN and the implementation under FPGA of the maximum entropy segmentation algorithm based on PCNN. The content can be divided into two parts concretely:1. By means of analyzing the parameter selection of a single neuron in PCNN and the nonlinear characteristic of PCNN, the PCNN model which can generate chaotic characteristic is chased down and analyzed. The stability control to the desired point of the chaotic model and tracking the reference point are studied. Experimental results show that PCNN can generate chaos, can reach the stable control according to desired control points, and can track the reference signal accurately.2. Taking the advantages of PCNN in image segmentation into account, the segmentation of three types of images based on PCNN is studied and the optimally segmented image is selected on the basis of the principle of maximum entropy. Compared to the algorithm simulation under MATLAB, the implementation of binary image segmentation based on PCNN is characteristic of high speed and strong real-time under the hardware platform of FPGA, while almost the same segmented images can be obtained. Moreover, compared to the traditional hardware implementation of PCNN, the speed under FPGA is increased significantly, so FPGA has the incomparable advantages over CMOS and is of better applied value.