HDB3

cpa algorithm for face recognition

matlab中的光学工具，实现光学仿真实例源代码(matlab optical tool)

用自适应方法，对ABR交通流的拥塞控制。(With adaptive methods, the ABR congestion control traffic flow.)

基于matlab的海洋通信的基础猜想，采用数字调制，2径仿真，其中损耗采用HUAWEI早年实测模型(Based on the basis of conjecture matlab marine communications, digital modulation, two-path simulation, in which the loss measured using early model HUAWEI)

The first scheme is based on the spatial locality of feature vectors corresponding to similar images. Learning is effected by modifying the query vector to incorporate the positive examples. The second scheme is based on “distorting” our view of the feature space. An new similarity distance between an image and the query is learned from the relevance feedback.

This M Code simulate the effects of clipping and filtering on PAPR PAPR reduction in OFDM-based wireless standard.Also the performance of BER versus SNR of original OFDM signals with PAPR reduction based on clipping and filtering schemes over AWGN channel is evaluated. The simplest and most widely used technique of PAPR reduction is to basically clip the part of signals that are outside the allowed region.Clipping methode introduces both in band distortion and out of band radiation into OFDM signals which degrades the performance including the BER and spectral efficiency.Filtering can reduce out of band radiation after clipping although it can not reduce in-band radiation distortion.However, clipping may cause some peak regrowth so that the signal after clipping and filtering will exceed the clipping level at some point.To reduce peak regrowth a repeated filtering and clipping operation can be used to obtain a desirable PAPR at a cost of computational complexity increase.

Dans la partie expérimentale, nous allons considérer un cas simple où l’espace de configuration est limité à 2 dimensions avec des obstacles ponctuels (réduits à des points). On va considérer un espace de configuration de taille 100x100, où l’on va disposer des obstacles ponctuels. Dans le code fourni (potentialfield.m), nous définissons deux structures : s et r. Ces structures possèdent trois champs : - x : correspond à la position du point (attracteur pour s et répulsif pour r) - w : le poids (ξ pour l’attracteur et η pour le répulsif) - k : le choix de la fonction heuristique (conique/parabolique pour l’attracteur, exponentielle/hyperbolique pour le répulsif) La variable q représente la position courante du robot. Les fonctions fieldplot et robotplot gèrent les affichages.

说明：  用来在视频中检测人体动作，包括了多种时空特征(Source code for human action detection in video)

Part I presents the fundamental concepts andMATLAB
programs for simulation of wireless channel modeling techniques, including large-scale fading, small-scale fading, indoor and outdoor channel modeling, SISO channel modeling, and MIMO channel modeling.

非负矩阵分解的一种新方法——Nesterov法，这种方法提出不久，实现的结果很不错(NMF is a new method--Nesterov method, this method is presented shortly to achieve very good results)