MM1

Dear Sir, I have upload some source codes of image processing & digital signal processing performed on matlab platform to avail the membership from you. Thank You.

its the data base loading file in matlab

说明：  数字音乐MATLAB处理，可以在MATLAB下进行混音，回响，延时，乐器的更改(Digital music MATLAB processing, can be carried out under the MATLAB mixing, echo, delay, musical instruments of change)

小波变换用计算机的快速实现，采用MATLAB计算工具(Wavelet transform fast to achieve using the computer，Using MATLAB calculation tool)

program to hep on analyse the multilevel inverterprogram to hep on analyse the multilevel inverterprogram to hep on analyse the multilevel inverterprogram to hep on analyse the multilevel inverter

用matlab实现用遗传算法解决VRPTW问题的算例源代码(Using matlab to realize the source code of an example of solving VRPTW problem with genetic algorithm)

对信号进行FFT、包络、峰值检波、PeakVue处理(The signal FFT, envelope, peak detector, PeakVue treatment)

说明：  本人提交的用matlab的关于滤波器设计的作业，很有用的　(I used Matlab submitted on the design of filter operation, a very useful)

基于LANDMARC的定位系统上进行的算法复杂度的减小的优化，包括了具体的优化后系统的实现，误差前后对比，改文章还提出了一种adaptive的定位算法，更利于外部变化环境下(In wireless networks, a client’s locations can be estimated using signal strength received from signal transmitters. Static fingerprint-based techniques are commonly used for location estimation, in which a radio map is built by calibrating signal-strength values in the offline phase. These values, compiled into deterministic or probabilistic models, are used for online localization. However, the radio map can be outdated when signal-strength values change over time due to environmental dynamics, and repeated data calibration is infeasible or expensive. In this paper, we present a novel algorithm, known as Location Estimation using Model Trees (LEMT), to reconstruct a radio map by using real-time signal-strength readings received at the reference points. This algorithm can take real-time signal-strength values at each time point into account and make use of the dependency between the estimated locations and reference points. We show that this technique can effectively accommodat)

svm 分类小例子，准确率较高。有可能是样本较少或者是样本数据取得太好的缘故。(svm classification)