sharpness-code

Elman神经网络：Elman网络是 J. L. Elman于1990年首先针对语音处理问题而提出来的, 它是一种典型的局部回归网络( global feed for ward l ocal recurrent)。Elman网络可以看作是一个具有局部记忆单元和局部反馈连接的前向神经网络。Elman网络具有与多层前向网络相似的多层结构。它的主要结构是前馈连接, 包括输入层、 隐含层、 输出层, 其连接权可以进行学习修正 反馈连接由一组“结构 ” 单元构成,用来记忆前一时刻的输出值, 其连接权值是固定的。在这种网络中, 除了普通的隐含层外, 还有一个特别的隐含层,称为关联层 (或联系单元层 ) 该层从隐含层接收反馈信号, 每一个隐含层节点都有一个与之对应的关联层节点连接。关联层的作用是通过联接记忆将上一个时刻的隐层状态连同当前时刻的网络输入一起作为隐层的输入, 相当于状态反馈。隐层的传递函数仍为某种非线性函数, 一般为 Sigmoid函数, 输出层为线性函数, 关联层也为线性函数。(Elman neural network: Elman JL Elman network is first proposed for speech processing problems in 1990. It is a typical local regression network (global feed for ward l ocal recurrent). Elman network can be seen as having a forward neural network of local memory unit and local feedback connections. Elman network has a multi-layer multilayer structure similar to the network. Its main structure is a feedforward connection, comprising an input layer, a hidden layer and output layer, which can be connected right learning correction feedback connected by a set of " structural" units, the output value of the memory for the previous time, which connection weights are fixed. In such a network, in addition to ordinary hidden layer, there is a special hidden layer, called an associative layer (or contact layer unit) this layer receives feedback signals the hidden layer, each hidden layer node has an associated layer node corresponding connection. The role of the associated layer is fo)

本程序采用8结点四边形单元，分析固定位移边界条件的弹性力学平面问题(This procedure using 8-node quadrilateral element, analysis of fixed displacement boundary conditions of the plane problem in elasticity)

针对四维图像原始数据矩阵通过matlab程序画图(4D figure)

采用模糊PD控制的系统仿真，提供了设计方案，(The fuzzy PD control system simulation, provides design,)

说明：  遗传算法 C语言源码Denis Cormier (North Carolina State University)开发的，Sita S.Raghavan (University of North Carolina at Charlotte)修正，很实用(GA C language source code Denis Cormier (North Carolina State University) developed, Sita S. Raghavan (University of North Carolina at Charlotte) amendments, it is practical)

王锡凡《电力系统规划》中采用等效电量函数法中，算例提供的matlab程序(PROCEEDINGS equivalent power function method is used in the power system planning, operator cases matlab program)

The performance coefficient depends on both the pitch angle (β) and the tip speed ratio (λ). The tip speed ratio is calculated by using blade tip speed and wind speed upstream of the rotor. The relationship between performance coeffi cient (c_p), pitch angle (β) and tip speed ratio (λ) is established by the c_p- λ approximation (3) for different blade pitch angle.

现有一个信号：x(n)=1+cos(π*n/4)+ cos(2*π*n/3)设计及各种数字滤波器以达下列目的： 低通滤波器，滤除cos(2*π*n/3) 的成分，即想保留的成分为1+cos(π*n/4) 高通滤波器，滤除1+cos(π*n/4) 的成分，即想保留的成分为cos(2*π*n/3) 带通滤波器，滤除1+cos(2*π*n/3) 的成分，即想保留的成分为cos(π*n/4) 带阻滤波器，滤除cos(π*n/4) 的成分，即想保留的成分为1+cos(2*π*n/3) 1. 用MATLAB命令butterord求除滤波器的阶数,用命令butter设计各滤波器；画出滤波器幅度和相频相应 取各滤波器的系统函数H(z)。 (an existing signal : x (n) = a cos (* n/4) cos (2** n/3) design and digital filter to achieve the following objectives : low-pass filter, filter cos (2** n/3) the ingredients that want to retain an element of a cos (* n/4) high-pass filter, a filter cos (* n/4) components, namely to retain the element of cos (2** n/3) band-pass filter , a filter cos (2** n/3) components, namely to retain the element of cos (* n/4) band stop filter, the filter cos (* n/4) components, namely to retain the ingredients for a cos ( 2** n/3) 1. MATLAB order butterord except for the band Filter, using the order of the filter design butter; paint Filter magnitude and phase frequency of the corresponding filter system function H (z).)

利用zhang suen快速并行的算法 实现了字符图像的细化功能 有较好的细化效果(Use of the the zhang suen fast parallel algorithm to achieve the refinement of character images function better refinement effect)

this program do qam modulation and upsampling and downsampling and use raised cosine filteroj