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matlab例程MATLAB 6.x版的内建数据类型（Built-in data type）就有5种以上，此外还有许多其他专门设计的类（Class），如符号类、内联函数类、控制工具包中的线性时不变模型类、神经网络类等。就程序设计而言，MATLAB 6.x版采用了面向对象编程技术。数据和编程的改变使用户能更简捷而自然地解决复杂的计算问题（如符号计算问题、多变量控制系统问题、神经网络问题）。本章内容根据MATLAB6.5编写，但绝大部分内容适用于其他MATLAB6.x版本。-Matlab routi
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Wouldn t it be great if we could somehow give visual commands to our computer without touching the keyboard or mouse? In this article, we will put together a simple laser gesture recognition application and use it to control Windows Media Player. Thi
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实验使用BP神经网络来逼近一个较复杂的正弦函数，并观察BP神经网络的各个参数对BP神经网络的影响.-Experimental use of BP neural network to approximate a more complex sine function, and to observe the parameters of BP neural network on the impact of BP neural network.
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神经网络实例集。包括以下几个程序单层线性神经网络实例、感知器神经元解决较复杂输入向量的分类问题、基于感知器神经网络处理复杂的分类问题、数值分析程序matlab-GUI、用BP网络完成函数的逼近源程序、自组织特征映射应用实例-Examples of neural network sets. Procedures include the following examples of single-layer linear neural network, perceptron neuron input
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* Lightweight backpropagation neural network.
* This a lightweight library implementating a neural network for use
* in C and C++ programs. It is intended for use in applications that
* just happen to need a simply neural network and do not
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这是神经网络算法的第二部分，有MATLAB编写，功能是复杂神经网络中的穷举算法，校赛是编写的-This is a neural network algorithm for the second part of the preparation have MATLAB, function is a complex neural network in the exhaustive algorithm, the school is prepared race
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倒立摆是一种复杂、时变、非线性、强耦合、自然不稳定的高阶系统，许多抽象的控制理论概念都可以通过倒立摆实验直观的表现出来。基于人工神经网络BP算法的倒立摆小车实验仿真训练模型，其倒立摆BP网络为4输入3层结构。输入层分别为小车的位移和速度、摆杆偏离铅垂线的角度和角速度。隐含层单元数16个。输出层设置为1个输出单元。输入层采用Tansig函数，隐含层采用Logsig函数，输出层采用Purelin函数。用Matlab 6.5数值计算软件对模型进行学习训练，并与线性反馈控制逻辑算法对比，表明倒立摆控制B
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一个复杂系统神经网络辨识,采用改进BP算法对随机噪声的二阶系统进行模型辨识,效果挺好的.-A complex neural network system identification, using BP algorithm to improve the random noise of the second-order system identification model, the effect of the good.
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This program simulates a 3 or 4-layer Neural Network, and can be used to
simulate an arbitrary, complex, or non-linear function that would be
difficult to implement by traditional methods. The Back Propagation
method is used "teach" the net
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在本讲义中，我们将着重讲述一些数学建模中常用的算法，包括神经网络算法、遗传算
法、模拟退火算法和模糊数学方法。用这些算法可以较容易地解决一些很复杂的，常规算法很难解决的问题。-In this lecture, we will focus on about a number of commonly used mathematical modeling algorithms, including neural network algorithm, genetic algorithm
Meth
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摘 要： 介绍BP算法神经网络由线拟舍方法，并借助MATLAB工具箱函数将它运用于方解石色散特性研
究，通过拟合效果图，误差曲线，误差范数反映BP神经网络的优越性，体现BP算法较高的预测能力和良好的泛化能
力，并且可以自动地确定数学模型．精确度高，原理也较简单，尤其对复杂的输入输出系统具有更好的效果。-Abstract： Curve fitting method of BP neural network was introduced and applied in the model of
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BP神经网络预测模型的非线性逼近功能很好，能够成功的预测复杂的数据结构-The BP neural network model of nonlinear approximate function is very good, can successfully predict complex data structure
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BP神经网络，包括由大量的简单基本元件——神经元相互联接而成的自适应非线性动态系统。每个神经元的结构和功能比较简单，但大量神经元组合产生的系统行为却非常复杂。-BP neural network，By a large number of simple basic components- neurons interconnected by adaptive nonlinear dynamic systems. The structure and function of each neuron is
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一些通过优化算法将BP神经网络进行优化后的代码，对于处理复杂数据有一定的优点。-Optimization algorithm BP neural network optimized code has certain advantages for the treatment of complex data.
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本文介绍在Matlab 环境下发电厂水位控制BP 模型的建模与仿真方法, 得出了预测模型的最优参数。仿真结果表明, MATLAB
神经网络工具箱可有效地用来解决复杂的非线性控制系统的优化设计问题。-This article describes the Matlab environment plant level control BP Model modeling and simulation methods, predictive models obtained optimal parame
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关于复杂网络的,基于MATLAB的BP神经网络的仿真与实现论文-On complex networks, simulation of MATLAB BP neural network and realization of papers! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
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This paper presents neural networks based approach
for estimation of the control and operating parameters of Statcom
used for improving voltage profile in a power system, which is
emerging as a major problem in the day-to-day operation of
stresse
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复数神经网络及其在说话人识别中的应用，及其matlab代码(Complex neural network and its application in speaker recognition)
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该代码为基于BP神经网络的预测算法。对于复杂的非线性系统，难以用数学方法准确建模，在这种情况下，可以建立BP神经网络表达这些非线性系统。(The code is a prediction algorithm based on BP neural network. It is difficult for complex nonlinear systems to be modeled accurately by mathematical methods. In this case, BP neura
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深度学习MATLAB的工具箱，包括CNN、RNN、CAE、LSTM等复杂的神经网络的代码。(Deep learning MATLAB toolbox, including CNN, RNN, CAE, LSTM and other complex neural network code.)
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