神经

Objective To research the treatment of delayed developing compression syndromes caused by pseudoneuroma or cicatrix in nerve trunk intramembrane,and to evaluate the outcome.

目的 探讨神经干膜内由于假性神经瘤或瘢痕组织引起的迟发进行性神经卡压综合征的临床特点和治疗方法。

Methods 58 cases were operated upon microsurgery to resect the pseudoneuroma or cicatrix and to repair nerve.Results The time of nerve recovery ranged from several hours to six weeks.

中文摘要：目的探讨神经干膜内由于假性神经瘤或瘢痕组织引起的迟发进行性神经卡压综合征的临床特点和治疗方法。

Neurologic improvement was achieved in all of the 24 patients with neural claudication and other neurologic findings.

在所有24例有神经源性跛行或其他神经症状的患者中，神经症状都得到了改善。

Neurologic improement was achieed in all of the 24 patients with neural claudication and other neurologic findings.

在所有24例有神经源性跛行或其他神经症状的患者中，神经症状都得到了改善。

Results and conclusion: the mathematics mechanism theory of Nervous system about their basic data and interconnection may be expressed by the neural information encoding formulation: x1=m1a/b and y1=n1c/d、x2=m2b/a and y2=n2d/c The neural information encoding formulation have novenary and undecimal and many other scales. All Periphery Nervous- Cerebral Cortex- Sympathetic Nervous have obvious and invisible encoding data in 2 kinds: yin and yang ,2kinds:ambulatory and static state, 3 grades: Max Med and Min. they all exist in obvious or invisible type. Just like a cogwheel system and there is a inter-meory function among the data.

结果与结论：神经系统基本数据及其相互关系的数学机制可用神经信息编码计算公式：x1=m1a/b与y1=n1c/d、x2= m2b/a与y2=n2d/c表达；神经信息编码计算有9与11等多种进位制；周围神经-大脑皮质-交感神经皆以隐性或显性型式存在阴阳两种静动两类大中小三级编组数据，犹如齿轮系统，数据之间起着互记功能；45对周围神经-54对大脑皮质分区-15对交感神经、脊神经前根与后根神经小束数之比3/5等神经系统基本数据皆是由数学计算机制决定形成。

It is defined that the two integrating ways' characteristics of the wavelet NN and theirs applying on the equipments' intelligence diagnose. Wavelet analysis technology has the ability of analyzing strongly the non-placidity signals' time-frequency, self-studying the NN, of dealing with data distributed and collaterally, of mapping non-linear ability, and it is fit for diagnosing failures.

利用小波分析对非平稳信号强的时频分析能力和神经网络的自学习、分布式并行处理数据及非线性映射能力，以及它们适合于故障诊断的特点，说明小波与神经网络的松散型和和紧致型结合途径下产生的两种小波神经网络的各自特点及其在设备智能诊断中的应用。

In this paper, the application of neural networks for industrial contrail control systems is introduced and the problem of building neural network model of the nonlinear control objects is described.

介绍了神经网络在工业控制系统中的应用；论述了建立非线性被控对象的神经网络模型问题；介绍了神经网络控制的主要方案，这些方案可用于过程控制和电气传动控制系统。

However, the conventional CMAC has an enormous memory requirement so that it cannot be applied to solve higher dimensional problems.

因此，本研究提出一个具有自组织能力之阶层式小脑模型类神经网路，它可以依据分析学习样本的分布，自动建立网路的记忆体配置，并藉由阶层式的学习架构，来有效降低记忆体的需求，使其具有解决高维度问题的能力，而此类神经网路架构亦具有可扩充性，可以在不影响其他网路的学习架构下，任意的增减输出节点的个数，此外，我们也提出了一个渐进式学习的演算法来训练此一类神经网路。

A fixed point of a discrete-time neural network with generalized input-output function and by using the converse theorem of Lyapunov function we study the uniformly asymptotical stability of equilibrium in this discrete-time neural network with variable weight and give some sufficient conditions that guarantee the stability of it.

本文首先介绍了几类离散神经网络模型的由来及其研究概况，利用Schauder不动点原理证明了一类具有广义输入输出函数的离散神经网络模型平衡点的存在性，利用Lyapunov函数逆定理给出了这类离散神经网络模型在时变权值下的一致渐近稳定性的充分条件。

In this thesis, we firstly introduce several class of discrete-time neural network models and the research progress of the neural networks. By Schauder fixed-point principle we prove the existence of an equilibrium (i.e. a fixed point) of a discrete-time neural network with generalized input-output function and by using the converse theorem of Lyapunov function we study the uniformly asymptotical stability of equilibrium in this discrete-time neural network with variable weight and give some sufficient conditions that guarantee the stability of it.

本文首先介绍了几类离散神经网络模型的由来及其研究概况，利用Schauder不动点原理证明了一类具有广义输入输出函数的离散神经网络模型平衡点的存在性，利用Lyapunov函数逆定理给出了这类离散神经网络模型在时变权值下的一致渐近稳定性的充分条件。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。