Understanding the dynamical characteristics of neural networks by universal fuzzy logical framework

The analytical study of a large scale nonlinear neural network is an uneasy task. We try to analyze the function of neural systems by probing into the fuzzy logical framework of the neural cells´ dynamical equations. Many papers investigate the relation between fuzzy logic and neural system. But most investigations focus on finding new function of neural system by combining fuzzy logical and neural system. In this paper, a novel approach is used to understand the nonlinear dynamic characteristics of neural system by analyzing the fuzzy logic framework of neural cells. It is the only way to understand the behavior of a large scale nonlinear neural system. By abstracting the fuzzy logical framework of a neural cell, our analysis enables the delicate design of network models. As an example, a difficulty task to build a recurrent network model of primary visual cortex by common dynamical analysis can be easily completed by this kind approach