symbol-error-rate-for-16-PSK-modulation

magnetic field from a straight wire

DRROBOT I90的基本應用以及智慧型影像錄相機無線移動系統(The basic application DRROBOT I90, and intelligent video recorder wireless mobile systems)

标准粒子群算法PSO,MATLAB中实验,对学习粒子群算法很有帮助(Standard particle swarm optimization PSO, MATLAB in experiments on learning PSO helpful)

RS粗糙集利用，用于特征属性的约减，用matlab实现的。(RS rough set utilized for feature attributes about subtraction, using matlab to achieve.)

自适应滤波的matlab代码，非常实用，可配合专门的书籍参考(Adaptive filtering matlab code, very practical, with special reference books)

sliding mode control files for advanced control system

基于纹理结构的图像检索，matlab实现。(Texture-based image retrieval, matlab achieve.)

非常不错的QPSK在matlab中的仿真教程，文档中包含相关的所有代码(very good QPSK in the Matlab simulation Guide, the document contains all the related code!)

classes in c++ and helps to learn the language

OTSU Gray-level image segmentation using Otsu s method. Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern. 9:62-66 1979). Thresholds are computed to maximize a separability criterion of the resultant classes in gray levels. OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the corresponding Iseg is therefore a binary image. The pixel values for Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ... [Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability criterion within the range [0 1]. Zero is obtained only with images having less than n gray level, whereas one (optimal value) is obtained only with n-valued images.