manghing_v74

This module will simulate any PV module with different weather conditions as an input. and is also connected to an simplified Maximum Power Point Tracker system to recognize the Working volrage of the cell (module)

比较QR分解算法与迫零算法的误码率，支持BPSK调制和QPSK调制，天线数量可以选择(Compare QR decomposition algorithm and zero forcing algorithm BER)

lpc 线性预测分析 可以计算不同帧位和阶数的语音线性预测结果和误差(lpc linear prediction analysis, we can calculate the order of the different frames of voice-bit and Linear Prediction results and error)

说明：  matlab与科学计算的教程编写的课堂课件(MATLAB and science calculational)

MAGNITUDE AND PHASE RESPONSE OF HIGH AND LOWPASS FILTER

高速铁路路基沉降是一个复杂的系统过程,涉及不同时期、不同工况,选用单一的预测模型不足以反映路基整体的变形规律.Logistic模型及Verhulst模型的曲线均为S形,可以反映全过程的地基沉降与时间的关系.针对路基填筑期和降水期两个时段利用MATLAB软件编制程序计算模型参数,得到Logistic模型和灰色Verhulst模型,进而求得两者的最优加权组合模型.对比结果表明:在路基填筑期由两者的最优加权组合模型预测得到的结果与实测结果较吻合,拟合精度高于单一模型 而在降水期Verhulst模型的预测值更接近实测值,平均相对误差约为1.75％,拟合精度较高.(High-speed railway subgrade settlement process is a complex system involving different times and in different conditions, the choice of a single forecasting model does not adequately reflect the overall deformation of roadbed. Curve Logistic model and Verhulst models are S-shaped, the whole process can be reflected foundation settlement versus time. against roadbed construction period of two hours and precipitation using MATLAB software programming model parameters, the Logistic model and gray Verhulst model, and then get the optimal model of a weighted combination of the two. comparative results indicate : results and experimental results in the roadbed construction period by the weighted combination of the best of both models predicted than the anastomosis fitting accuracy than a single model precipitation predicted value of Verhulst model closer to the actual value of the average relative error approximately 1.75 fitting accuracy.)

广义高斯模型参数估计，效果相当不错！ 广义高斯模型参数估计，效果相当不错！(general gaussian parameters estimate)

基于matlab 的模拟退火算法源程序，经典算例，有PDF说明。(Based on the simulated annealing algorithm matlab source, the classic example, a PDF note.)

LFM 抽取处理 D=5 LFM加SNR=10dB LFM加10dB噪声抽取输出需加滤波器(LFM draw sample D=5，LFM was added with noise，and SNR=10dB)

说明：  一本MATLAB-Labviewsystemview方面的书籍。(A MATLAB-Labviewsystemview of books.)