PSO

本书包含MATLAB使用和数学知识的丰富层次。编著本书有四个主要目的：（1） 帮助初学者顺利跨入MATLAB大门；（2） 全面、多层次、细致而深入地叙述MATLAB中数值、字符串、胞元、构架、逻辑、函数句柄六种重要数据类型的应用规则、相互配用和编程规范；（3） 由浅入深地阐述MATLAB三种建模、分析、仿真环境——数值计算、符号计算和Simulink环境的特征和使用要领；（4） 以实例讲述MATLAB代表的现代计算能力对传统算法和思维的影响。(Book contains rich levels of using MATLAB and mathematics knowledge. Compiled the book has four main purposes: (1) help beginners MATLAB entered the door smoothly (2) comprehensive, multi-level, meticulous and thorough account Numbers, strings, cell yuan, in the MATLAB framework, logic and function handles six important application rules, with each other and programming of the data type specifications (3) describes the MATLAB distinguished three kinds of modeling, analysis, simulation environment, numerical and symbolic computation and Simulink environment characteristics and use of the essentials (4) with examples about MATLAB on behalf of the modern computing power s influence on the traditional algorithm and thinking. )

64QAM的基带系统仿真，计算随机0、1数据经64QAM调制后的星座图，8倍上采样后图形，滤波后图形，接收端图形，比较不同信噪比下的误码率(64QAM baseband system simulation, calculation data randomly 0,1 modulated by 64QAM constellation, the 8 times the sampled pattern, filter pattern graphic receiving end, error rate under different SNR)

说明：  关于matlab对通信系统建模与仿真的应用(Matlab on the communication system on the Modeling and Simulation Application)

在矩阵或者二维图像中画一个圆,没有丢失的像素点 (Draw a circle in a matrix/image)

MATLAB学习，PPT文件。完全深入简出的教学方法，从最简单的着手。(MATLAB Learning, PPT files. Completely in-depth Jane out of teaching methods, from the simplest place to start.)

matlab命令行环境的常用操作 再发个详细的，大家帮忙给顶顶 (Matlab command line environment of commonly used operating again issuing a detailed, after another to help everyone)

matlab中对图形轮廓的特征提取代码，程序实现，(matlab in the graphic outline feature extraction code, program implementation,)

哈尔滨工程大学研究生随机过程实验作业，里面有作业matlab源程序(Harbin Engineering University Graduate random process lab assignments, which has an operating matlab source)

matlab code for stereo coding

Abstract—Numerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular.