bpsk

svpwm，三电平，simulink，空间适量脉冲宽度调制(svpwm, three-level, simulink, space right amount of pulse width modulation)

说明：  这是一个维纳滤波器设计的程序，用matlab语言实现。(This is a Wiener filter design program, complete with matlab language.)

这是用MATlab进行用户界面设计的程程序这是界面的功能是：对连续时间函数w(t)=exp(-abs(t))在【-5，5】区间内进行采样，利用样条插值重构该连续函数，绘出重构图形并输出重构误差。(It is used MATlab process of user interface design process which is the interface functions are: a continuous time function w (t) = exp (-abs (t)) in the range】 【-5,5 samples, using spline Reconstruction of the continuous interpolation function, draw the reconstruction graphics and output reconstruction error.)

基于Wiener滤波的语音消噪Matlab源程序 调用方式： output=WienerScalart96(signal,fs,IS) signal－－输入含噪语音 fs－－－－语音信号采样率 IS－－－－起始静音端，用来估计噪声方差（秒做单位，默认是0.25秒） (Wiener filter-based de-noising of the voice call Matlab source code the way: output = WienerScalart96 (signal, fs, IS) signal- voice input with noise fs---- voice signal sampling rate IS---- Start mute end used to estimate the noise variance (units of seconds to do, the default is 0.25 seconds))

简单蚁群算法解决tsp问题 一共有48城市 花费7分钟(Simple ant colony algorithm to solve the problem 1 tsp spent a total of 48 cities in 7 minutes)

matlab时频分析工具箱，时频分析工具箱包括短时傅立叶变换和二次型时频分析以及各种时频分析的matlab代码(The Time-Frequency Toolbox (TFTB) is a collection of about 100 scripts for GNU Octave and Matlab (R) developed for the analysis of non-stationary signals using time-frequency distributions. It is primary intended for researchers and engineers with some basic knowledge in signal processing.)

Digital Signal Processing Charles Darwin University Lab9

How the K-mean Cluster work Step 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (N-k) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3 . Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4 . Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments. (How the K-mean Cluster workStep 1. Begin with a decision the value of k = number of clusters Step 2. Put any initial partition that classifies the data into k clusters. You may assign the training samples randomly, or systematically as the following: Take the first k training sample as single-element clusters Assign each of the remaining (Nk) training sample to the cluster with the nearest centroid. After each assignment, recomputed the centroid of the gaining cluster. Step 3. Take each sample in sequence and compute its distance from the centroid of each of the clusters. If a sample is not currently in the cluster with the closest centroid, switch this sample to that cluster and update the centroid of the cluster gaining the new sample and the cluster losing the sample. Step 4. Repeat step 3 until convergence is achieved, that is until a pass through the training sample causes no new assignments.)

设计一个按照时间抽取的基2快速傅里叶变换（基2FFT-DIT）。输入倒位序，输出自然顺序。(To design a time of extraction according to the base 2 Fast Fourier Transform (base 2FFT-DIT). Input inversion sequence, the output natural order.)

数字信号处理,对与初雪着很有用,注释非常详细,调试都通过了!(Digital signal processing, with the first snow of the very useful, very detailed notes, debugging are adopted!)