The binding problem is regarded as one of the central themes of cognitive science and neuroscience. In order to solve the binding problem of shapes and colors for color images

an advanced vector model for the binding problem

based on the simplified pulse coupled neural network(PCNN)

is presented in this paper. In this model

the first pulse emission time of a neuron separates the different characteristics

while the input stimulus of the neurons itself binds the different characteristics. The experimental results indicate that the model can achieve good feature separation as well as feature binding and it discovers the optimal iteration times. The method has certain reference value for the research and application of the binding problem of color image.