yundong

　计算机人脸识别技术( Face Reocgnition)就利用计算机分析人脸图像,从中提取出有效的识别信息,用来辨认身份的一门技术。[ 1 ]即对已知人脸进行标准化处理后,通过某种方法和数据库中的人脸样本进行匹配,寻找库中对应人脸及该人脸相关信息。人脸自动识别系统有两个主要技术环节,一是人脸定位,即从输入图像中找到人脸存在的位置,将人脸从背景中分割出来,二是对标准化后的人脸图像进行特征提取和识别。本文中介绍的PCA (特征脸)方法就是一种常用的人脸 特征提取方法。(Computer Face Recognition Technology (Face Reocgnition) on the use of computer analysis of facial image, to extract the valid identification information used to identify the status of a technology. [1] that is known to standardize treatment of face, through a method and a database of face samples for matching, search library, the corresponding face and the face-related information. Automatic face recognition system has two main technical aspects, first, face location, that is, from the input image to find the location of the face there, the faces will be split out from the background, the second is, the standard features of face images extraction and recognition. Described in this paper PCA (Eigenfaces) method is a common facial feature extraction method.)

这是接着上一次的一些大家很可能用到的聚类分析方法，有PCA等，希望能给大家一些帮助。(then this is the last time some people may use the cluster analysis method, PCA. I hope that it provides some help.)

inter-process communication (IPC) is a set of methods for the exchange of data among multiple threads in one or more processes. Processes may be running on one or more computers connected by a network. IPC methods are divided into methods for message passing, synchronization, shared memory, and remote procedure calls (RPC). The method of IPC used may vary based on the bandwidth and latency of communication between the threads, and the type of data being communicated.

Clark变换与Inv_Clark变换，引入输入信号进过测试能够实现功能(Clark and Inv_Clark)

S. Haykin：自适应滤波器原理第四版的matlab代码(S. Haykin: Adaptive Filter principle of the fourth edition of the matlab code)

摘要 该文主要考虑利用图像噪声再生技术来提取图像细节 其思想是利用被滤除的噪声信号进行回收再利用 通过对噪声信号和初步去噪信号进行小波变换 比较它们的小波系数 当噪声信号的小波系数达到一定的阈值时 将噪声信号的小波系数保留叠加至初步去噪信号的小波系数 然后利用传统的软阈值去噪的方法来进行图像的去噪 从而达到既能够去除噪声 又能保留图像细节的目的 实验证明 该方法较传统的方法在去噪和细节保持上有改进(Abstract In this paper, consider using images to extract the noise regeneration of its ideological image detail is the use of the noise signal was filtered to recycle through the noise signal and the initial wavelet transform de-noising signal comparison of their wavelet coefficients of the wavelet signal when the noise coefficient reaches a certain threshold will be the noise signal superimposed to the wavelet coefficients to retain the initial de-noising signal wavelet coefficients and then using the traditional soft-threshold denoising approach to image denoising in order to achieve the removal of noise can not only be able to retain The purpose of image detail that the methods of the experiment a more traditional approach to denoising and detail in there to keep improving)

example about vibration

卡尔曼滤波器完成多传感器融合算法，不同机器人的不同传感器对足球位置进行估计，融合不同传感器数据得到精确估计(Kalman filter to complete the multi-sensor fusion algorithm, the different sensors of the robot football position estimates, the integration of different sensor data accurate estimate of)

particle swarm optimization for loss reduction

无线传感器基于LEACH协议的matlab仿真！(Based on matlab LEACH protocol for wireless sensor simulation!)