gaosi-kuosan-qiti-wuran-matlab

TDOAAOA定位的扩展卡尔曼滤波定位跟踪算法Matlab源码(TDOAAOA positioning location and tracking extended Kalman filter algorithm for Matlab source code)

用matlab编写的bpsk调制的dsss信号(Bpsk written by matlab signal modulation dsss)

利用matlab开发的机床直线和圆弧插补程序，可以进行四个象限的优劣圆弧，顺逆圆弧插补，同时可使用逐点比较法和数字积分法两种方法插补，软件界面简单明了、清楚，易操作。(The use of MATLAB development of machine tool of linear and circular interpolation procedures, can be carried out in four quadrants of the pros and cons of circular, clockwise arc interpolation, at the same time using point by point comparison method and digital integration method of two kinds of interpolation, the software interface is simple, clear, easy to operate.)

ansys三维建模，针对三维模式，施加涡流进行电磁场仿真分析(ansys 3D modeling, for a three-dimensional model, applied electromagnetic field eddy simulation)

4万亿投资的数模论文与实现的源代码，自己在学习数模课程的作业(4 trillion investment in digital to analog Papers and the source code, in the course of the digital-analog operations)

FIR与IIR滤波器在DSP上的实现.　　　DSP是利用计算机或专用DSP处理器，以数字形式对信号进行采集、变换、滤波、估值、增强、压缩、识别等处理，以得到符合人们需要的信号形式。FIR(Finite Impulse Response)滤波器：有限长单位冲激响应滤波器，又称为非递归型滤波器，是数字信号处理系统中最基本的元件，它可以在保证任意幅频特性的同时具有严格的线性相频特性，同时其单位抽样响应是有限长的，因而滤波器是稳定的系统。(FIR and IIR filter is implemented on the DSP. DSP is the use of a computer or a dedicated DSP processor in digital form to the signal acquisition, conversion, filtering, valuation, enhancement, compression, recognition processing needs of the people to give signal form. FIR (Finite Impulse Response) filter: finite impulse response filter units, also known as non-recursive filters, digital signal processing system is the most basic element, it can guarantee any amplitude-frequency characteristics of both a strict linear phase-frequency characteristics, while the unit sampling response is of finite length, and thus the filter is stable system.)

用matlab的Simulink对cdma2000中信道编码进行仿真 主要是turbo码部分。可能要用matlab7。0打开。(using Matlab Simulink right cdma2000 Channel Coding simulation is part of turbo codes. It may take matlab7. 0 Open.)

It is demonstrated that neural networks can be used effectively for the identification and control of nonlinear dynamical systems. The emphasis is on models for both identification and control. Static and dynamic backpropagation methods for the adjustment of parameters are discussed. In the models that are introduced, multilayer and recurrent networks are interconnected in novel configurations, and hence there is a real need to study them in a unified fashion. Simulation results reveal that the identification and adaptive control schemes suggested are practically feasible. Basic concepts and definitions are introduced throughout, and theoretical questions that have to be addressed are also described

自己编写的多项式拟合程序，阶数可选择，里面含有一个数据文件，下载即可运行，使用过程中也可以用自己的数据。(themselves prepared polynomial fitting procedure, the option order, which contains a data file can be downloaded operation, the use of the process can also use their own data.)

基于matlab的hmm语音实验平台，包含了众多的实验程序，为语音识别工作提供参考(Matlab-based the hmm Voice experimental platform, contains a large number of experimental procedures, and provide a reference for the voice recognition work)