An Analog CMOS Pulse Coupled Neural Network for Image Segmentation

摘要：

A novel CMOS pulse coupled neural network (PCNN) circuit based on Integrate and Fire (IAF) model is proposed in this work for image segmentation. The network consists of IAF neurons and weight adaption circuit which represents the interaction between neurons. The IAF neurons exhibit the electrochemical dynamics of natural biological neurons. According to achieve the adaption of both weights between two neurons, the weight adaption circuit can adjust the frequency and phase of the pulse stream generated by the neurons. Then the network can implemented for image segmentation. The HSPICE simulation results show that the frequency and phase of the pulse stream generated by the neurons with similar inputs are able to be synchronized, which indicates that this network may provide substantial advantages for image segmentation.

作者: Ying Xiong Wei-Hua Han Kai Zhao Yan-Bo Zhang Fu-Hua Yang

作者单位: Institute of Semiconductors, Chinese Academy of Science, Beijing 100083, China

会议类型: 国际会议

会议名称: 2010 10th IEEE International Conference on Solid-State and Integrated Circuit Technology(第十届固态和集成电路技术国际会议 ICSICT-2010)

会议地点: 上海

会议语种:英文

页码: 1883-1885

在线出版日期: 2010-11-01（万方平台首次上网日期，不代表论文的发表时间）