并联机器人运动学正逆解程序

一种用于非同步采样下的通信时，通过误差测量算法和多项式插值以达到同步的目地的论文。来源于I(A non-synchronous sampling of communications, through error measurement algorithm and polynomial interpolation in order to achieve synchronization of the thesis purpose. From I)

一个最速下降法实现例子，有需要的可以看看(A steepest descent method to achieve an example, there is need to take a look at)

MATLAB/SIMULINK

用wavedec2()函数对b1,b2两幅图像进行小波分解, 采用’db1’小波,分解到第三级 融合两幅图像。(With wavedec2 () function b1, b2 the two images were decomposed using ' db1' wavelet decomposition to the third level fusion of two images.)

研究中我么采用分段的方法对数字音频信号嵌入水印。为便于研 究，以灰度图像为数字水印原始信号经二值化处理后得到水印再嵌入 音频信号的离散变换域中，从而得到嵌入水印的音频信号，其实现过 程原理框图如图1 所示。在水印嵌入的过程主要实现四个阶段的任 务：(1)数据准备与预处理，主要是准备好水印原始图片和待嵌入水印 的音频信号 (2)音频信号分段处理，用于嵌入水印的音频数据部分等 分成(m1*m2)个音频数据段 (3)水印图像降维处理，在此过程灰度图像 水印转化为二值图象, 要将其嵌入到一维的数字音频信号中, 必须将 二维的图像转化成一维的序列 (4)将水印嵌入到数字音频信号中,从而 最终获得带数字水印的音频信号。(The study I Mody, segmented digital audio signal embedded watermark. Discrete transform domain to facilitate the study of the grayscale image for the digital watermark the original signal is obtained after the binarization processing watermark embedded in the audio signal, thereby obtaining the watermark embedded in the audio signal, and its implementation process schematic block diagram shown in Figure 1. Mainly in the watermark embedding process to achieve the task of four phases: (1) The data preparation and pretreatment, is ready to watermark the original picture and to be embedded in the audio signal of the watermark (2) audio signal segment processing for embedding watermark The audio data portion is divided into (m1* m2) audio data segment (3) The watermark image dimension reduction processing, binary image is converted to grayscale image watermark in this process, and to be embedded into a digital audio signal of a one-dimensional , two-dimensional images must be converted in)

DTMF+双音多频的matlab实现程序（带注释）(DTMF matlab code)

应用四阶龙格库塔法求解微分方程的初值问题(Applications fourth-order Runge-Kutta Solving Ordinary Differential Equations)

this code on C ANSI develop the product between matrix A*A, A*B, B*A.

LCMV代码，以及LCMV转化为广义旁瓣相消器的代码，这两种方法是等价的。(LCMV code and LCMV code is converted into a generalized sidelobe canceller, the two methods are equivalent.)

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。 该方法的关键是经验模式分解，它能使复杂信号分解为有限个本征模函数（Intrinsic Mode Function，简称IMF），所分解出来的各IMF分量包含了原信号的不同时间尺度的局部特征信号。经验模态分解法能使非平稳数据进行平稳化处理，然后进行希尔伯特变换获得时频谱图，得到有物理意义的频率。(The Empirical Mode Decomposition (EMD) method is considered as a major breakthrough in the linear and steady state spectrum analysis based on Fu Liye transform in 2000. The method is based on the time scale characteristics of the data itself to decompose the signal without setting any base functions in advance. The key of this method is the empirical mode decomposition, which can decompose the complex signal into a limited eigenmode function (Intrinsic Mode Function, for short, IMF), and the decomposed IMF components include the local characteristic signals of the different time scales of the original signal. The empirical mode decomposition method can smooth the non-stationary data, and then obtain the time-frequency spectrum by Hilbert transform to get the physical meaning frequency.)