We , in chapter 4 , comprehensively discuss the dynamics of discrete chaotic neural networks , including f the existence of fixed points , the stable , unstable dynamics of the fixed point , the saddle - node and period doubling bifurcations in singie neuron model , and chaotic dynamics of the networks . the proofs and de - ductions involve schauder fixed point principle , constructions of lyapunov func - tions , bifurcation theory , contraction map principle , and anti - integrable limit method 在本文的第四章中，我们首先介绍了离散混饨神经元、神经网络模型由来与具体的数学模型，依次给出了该离散神经网络的中不动点存在性与惟一性的分析：稳定性与不稳定性的分析；神经元模型的分枝分析；神经网络中马罗陀意义下混3屯动力学的分析
Firstly , the basic theories of artificial neural network are introduced , including neural cell model , the basic structure of artificial neural network and the study methods . the essential of bp network with function approximation and rbf network and the performance of technology are analyzed . the algorithm of bp and rbf networks are also studied 论文首先阐述了神经网络的基本理论,包括神经元模型,神经网络的基本结构和神经网络的学习方法;分析了具有函数逼近能力的bp网络和径向基函数( rbf )网络实质、技术实现问题,并研究了bp和rbf网络学习算法。
Besides , we show the method and result in the research of the heart rate variability . it is proved that the nonlinear analysis is much more effective in the clinical diagnoses of heart disease . by the end of this dissertation , we list some problems for our future works including chaos in discrete time ~ varying systems , srb measures of the chaotic map in the sense of marotto , complex dynamics of both h . h . model and cou - pled integrate - and - fire models , strange attractors in h6non systems with classical parameters 在本文的第五章中，我们给出了一类一维时滞泛函微分方程稳定性的判别法，而这一方程本身可以用来刻画连续的具有动态阈值的神经元模型；此外，我们介绍了非线性指标在心律变异中的具体应用与部分的分析结果，以进一步说明非线性分析在心律变异研究中的有效性和实用性
