| 1. | Three valued logic neuron model and its reasoning
三值逻辑神经元模型及推理 |
| 2. | Then , we give some basic information about the neuron model we studied which given by hodgkin and huxley
然后，我们给出所研究的模型? hodgkin - huxley ( hh )神经元模型的一些基本知识。 |
| 3. | In this case , the author puts forward to new aon - linear neural networks for classing - cc model and its network architecture
为此作者提出了新的用于分类学习的非线性神经元模型- - cc模型以及相应网络结构。 |
| 4. | 2 . the basic theories of neuron model - free control are introduced , which includes the neuron model for control , the learning strategy and the neuron control method . 3
介绍了神经元非模型控制的基本理论和方法，包括面向控制的神经元模型、学习策略、神经元控制系统的一般结构和神经元非模型控制的基本方法； 3 |
| 5. | By analyzing limitation of the traditional neural network , this paper presents intelligent neuron model based on linear independently function . the knowledge storing capacity of the intelligent neuron is analyzed
在分析传统神经网络缺陷基础上，运用线性独立函数构建了智能神经元模型，并对这种神经元的知识存储能力进行了理论分析。 |
| 6. | Second , according to the characteristic of the instantaneous change of action potential accompanied by the nerve impulse , we use h - h equation to describe such change , and conduct simulation combined with sr theory
然后根据产生神经冲动时动作电位全或无式瞬时快速变化的特点，采用h - h方程作为描述这种变化的神经元模型，结合随机共振理论进行了仿真研究。 |
| 7. | Fifthly , this paper proposes the model of three - rank chaotic neural network , its chaotic characteristic is simulated . the optimization parameter of non - line chaotic neural element model and neural network model with transient chaotic behaviors are discussed
建立了三阶混沌神经网络模型，并对其混沌特性进行了数值模拟；仿真分析了非线性混沌神经元模型的混沌特性；探讨了暂态混沌神经网络模型参数的优化选取。 |
| 8. | Based on fuzzy number nn , the model of fuzzy chaotic neuron is proposed in this paper , whose dynamics characteristics also have been analyzed thoroughly . the method how to build fuzzy chaotic neural networks ( fcnn ) with fuzzy chaotic neurons is also given
基于模糊数神经网络的实现方法，本文提出一种模糊混沌神经元模型，详细分析了其特性，并且给出了构建模糊混沌神经网络以及确定混沌神经网络联接权值的方法。 |
| 9. | Besides stability , bifurcation and chaos in neural networks have receiving much attention recently . in this dissertation , we propose two neuron models with chaotic dynamics , which constitute chaotic neural networks that encompassed various associative and back - propagation networks
除了稳定性之外，极限环以及混沌也是神经网络动态行为研究的重点，本文构造了具有混沌解的两种神经元模型，通过混沌神经元的耦合可以构成混沌神经网络。 |
| 10. | After we present the concepts of " coherence resonance " and " stochastic resonance " , to further study the hh neuron model , we introduce some properties of the hh equation , for example , the threshold of neuron ' s exciting , the responses of neuron toward different stimulations
在介绍了“相干共振”和“随机共振”的一些概念后，在hh神经元模型的基础上，本文给出了hh方程的一些特性，比如说神经元的兴奋有阈值，在受不同刺激时有不同的响应等。 |
