windpower

曲线拟合和多项式拟合-1，主要用于工程计算，工程优化。(Curve fitting and polynomial fitting, is mainly used for engineering calculations, engineering optimization.)

Crowd Event Detection in Computer Vision.pdf

code for matlab simulation o fsensor nettworks

一个详细的matlab图像处理教学, 是某重点大学的课件 仅供参考(A detailed matlab image processing instruction, a key university courseware)

用lin法求高阶方程，可解特征方程, 可以是两队复根，可以是一对复根和两个实根，也可以是四个实根。(lin method, solve latent function)

学习Ruby特全的电子书。大多都是英文的，有一本是中文。(Many e-books for learning Ruby language.)

本资料介绍了图论的概念，以及图论的用法，也包含了算法的matlab实现(Graph Theory matlab)

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)

智能天线自适应算法，该算法是基于DOA分解的MVDR算法。(Smart antenna adaptive algorithm that is based on the the DOA decomposition MVDR algorithm.)

這是一個可以自動尋找图像中的長方形, 正方形, 圓形, 菱形的程式(1- Read the RGB (colored) image in from user. 2- Convert image from (RGB) colored to gray image. 3- Threshold the image (convert gray image to binary image). 4- Invert the binary image (in order to speed up the time of processing). 5- Find the boundaries concentrate. 6- Determine shapes properties (ratio of dimensions, roundness). 7- Classify shapes according to its properties. )