spider20060724

比较均匀量化和A律13折线编码的信号量噪比，通过比较可以看出两者的区别。但不知道正不正确(A law more uniform quantitative and broken line 13 the amount of coded signal to noise ratio, can be seen by comparing the difference between the two. But do not know is not correct)

在matlab中用到的函数，用来方便构造小波和尺度函数(The function of the matlab in use, easy to construct wavelet and scale functions)

采用自相关函数法求基音周期，将采样得到的声音信号按每20ms一帧分为若干帧，并对每帧的序列求自相关函数，取自相关函数第一个最大值点算出基音周期，并以帧为横坐标，基音周期为纵坐标画图，并去除野点，最后取图中浊音部分即面积较大部分的值作为基音周期。(Using the autocorrelation function method pitch period, the sound signal is sampled every 20ms frame is divided into a plurality of frames, and each frame sequence uates the autocorrelation function, taken the first maximum point of correlation function calculated the pitch period, and frame as the horizontal, the vertical axis pitch drawing and remove outliers, and finally take the value of the area that is part of a larger portion of the figure as voiced pitch.)

说明：  K分布仿真的一部分，一部分是斑纹分量 还有是结构分量 两者点乘得到K分布序列 (K distribution part of the simulation, in part, there is a structural component markings component of both the dot distribution sequence obtained K)

与前边的程序配套使用，模拟实现小波去噪。(And in front of the program to simulate the matching, wavelet denoising.)

毕设内容，高光谱图像基本处理，使用matlab实现智能预测控制算法，包括最小二乘法、SVM、神经网络、1_k近邻法。( Complete set content, basic hyperspectral image processing, Use matlab intelligent predictive control algorithm, Including the least squares method, the SVM, neural networks, 1 _k neighbor method.)

模糊控制的算法设计，本程序已经经过调试，程序中有中文解析； (Fuzzy control algorithm design, this process has been debugging the program in Chinese analysis )

PCA又为主成分分析，是一种特征提取方法， 它通过线性变换寻找一组最优的单位正交向量基，用他们的线性组合来重构原样本(PCA and the main component analysis, a feature extraction method, which by finding a set of optimal linear transformation unit orthogonal base vectors, with their linear combination to reconstruct the original sample)

application note for sensor driver development

qpsk的调制解调源码，注释详细。功能正常。很适合学习调制解调的人.文件包含： qpsk_mod_demod.m(qpsk mod and demod procedure qpsk_mod_demod.m)