摘要： 针对视觉感知中特征的捆绑问题，在传统脉冲耦合神经网络(PCNN)的基础上，提出一种基于强度的PCNN模型。在该模型中，神经元邻域内脉冲发放总强度将不同的特征分离开来，而神经元自身的脉冲发放强度又将属于同一感知对象的不同特征捆绑起来。仿真结果证明，该模型可以实现特征的分离和捆绑。

关键词: 特征分离, 特征捆绑, 视觉感知, 脉冲耦合神经网络

Abstract: In view of feature binding in visual perception, this paper presents an advanced Pulse Coupled Neural Network(PCNN) model based on traditional PCNN. In this model, the pulse of the total strength in the neighborhood of neuron makes different characteristics separate, while the pulse of strength of neuron itself makes different characteristics bind. Simulation result indicates that the model can achieve feature separation and binding, so that it accomplishes the task of feature binding in visual perception and provides certain reference value for further research of feature binding in visual perception.

Key words: feature separation, feature binding, visual perception, Pulse Coupled Neural Network(PCNN)

中图分类号: 

• TP391.9