conv

关于小波变换的Mallat运算，是一维数据的Mallat(On the Mallat wavelet transform computing, data is one-dimensional Mallat)

in this code random noise is denoise by wavelet and find the parameter for best wavelets

说明：  MATLAB实现的NARX模型辨识程序，适用于初学模型辨识的学者理解NARX模型辨识方法(The NARX model identification program implemented by MATLAB is suitable for the scholars who are learning model identification to understand the NARX model identification method.)

是本科毕设的题目，基于掌纹识别的在线身份验证 识别算法本科毕设，内含心电信号数据及运用MATLAB写的源代码。( The title of the commercial is undergraduate course you Verify recognition algorithm based on palmprint recognition undergraduate complete set of online identity, ECG data and includes source code written in MATLAB.)

对不同源节点到中继节点距离的固定DF译码转发协作通信的误码率进行了仿真(The error rate of fixed DF decode and forward cooperative communication is simulated for the distance from heterogeneous nodes to relay nodes)

基于matlab2013a的simulink仿真，包括改进型插入式重复控制、pdff以及电机矢量控制仿真程序，为达到好的效果有些参数需要自己调试，希望大家的学习有所帮助～。(Based matlab2013a the simulink simulation, including improved plug-in repetitive control, pdff and motor vector control simulation program, in order to achieve good results and some parameters need to own debugging, we hope to learn some help ~.)

genatic algorithm code

阵列信号处理MATLAB代码,music算法，含有均匀圆阵、均匀线阵、均匀平面阵的代码；doa估计，来预测波达方向，信号的相关参数；(Array signal processing MATLAB code, music algorithm containing uniform circular array, uniform linear array, the uniform planar array code of doa estimated to predict the direction of arrival of the relevant parameters of the signal )

4阶经典Runge-Kutta格式解常微分方程,Romberg(龙贝格）法求函数的积分,三阶样条插值（一阶导数边界条件）,定步长梯形法求函数的积分,矩阵A的伴随矩阵, Lagrange插值法数值求解,Newton迭代法解非线性方程f(x)=0(Fourth-order Runge-Kutta classic format solution of ordinary differential equations, Romberg (Romberg) method for function points, third-order spline interpolation (first derivative boundary conditions), fixed-step trapezoidal method for integrating functions, matrix A adjoint matrix, Lagrange interpolation method for numerical solution, Newton iterative method for solving nonlinear equations f (x) = 0)

In computer science and information theory, Huffman coding is an entropy encoding algorithm used for lossless data compression. The term refers to the use of a variable-length code table for encoding a source symbol (such as a character in a file) where the variable-length code table has been derived in a particular way based on the estimated probability of occurrence for each possible value of the source symbol. It was developed by David A. Huffman while he was a Ph.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".