final_zerocrossing

Mean to calculate the digital filter.

suport vector regresion in matlab

说明：  经验模态分解（Empirical Mode Decomposition，简称EMD))方法被认为是2000年来以傅立叶变换为基础的线性和稳态频谱分析的一个重大突破，该方法是依据数据自身的时间尺度特征来进行信号分解，无须预先设定任何基函数。这一点与建立在先验性的谐波基函数和小波基函数上的傅里叶分解与小波分解方法具有本质性的差别。(Empirical mode decomposition (EMD) method is considered as a major breakthrough in linear and steady-state spectrum analysis based on Fourier transform since 2000. This method decomposes signals according to the time scale characteristics of the data itself, without setting any basis function in advance. This is essentially different from Fourier decomposition and wavelet decomposition based on prior harmonic basis function and wavelet basis function.)

v-blast4x4_dast程序，用于mimo信道闭环系统中，加入旋转矩阵贺信道dast编码,用于提高信道容量和误比特性能(v-blast4x4_dast procedures for MIMO channel closed-loop system, by adding rotation matrix Road DAST letter codes, used to improve channel capacity and BER performance)

说明：  阵列天线中music的实现代码,为毕业设计准备(Array implementation of the code in music, preparing for the graduation project)

matlab 频谱分析matlab 频谱分析matlab 频谱分析matlab 频谱分析matlab 频谱分析(matlab matlab spectrum analysis spectrum analysis spectrum analysis matlab matlab matlab spectrum analysis spectrum analysis)

function Invariant_Line_Feature_Matching ___DESCRIPTION___ Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? ) Example : Invariant_Line_Feature_Matching ( ) ___REFERENCE___ Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach Park, Lee, Lee - Ideal - CV and Im. Und. - 77, 263-283 - (2000)( function Invariant_Line_Feature_Matching ___DESCRIPTION___ Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? ) Example : Invariant_Line_Feature_Matching ( ) ___REFERENCE___ Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach Park, Lee, Lee- Ideal- CV and Im. Und.- 77, 263-283- (2000))

利用VC++6.0开发matlab与VC通信，本人已运行，好用(VC++6.0 developers Matlab and VC communication, I have to run, easy to use)

构造一个空的双向栈，判断双向栈是否存在，出栈，入栈，判栈空，将栈置空，判栈满，取栈顶(Construct an empty two-way stack to determine whether there is a two-way stack, out of stack, stack, sub-stack empty, set the stack is empty, sub-stack is full, take the stack)

这是我另一个同学的关于图像处理与机器学习的作业，对四组图像提取特征值，进行分类识别。LIBSVM.文件里包含代码，及一些参数调试。(This is another of my classmates on image processing and machine learning operations on four sets of image feature extraction values ​ ​ for classification. LIBSVM. File contains the code, and some parameters debugging.)