fractal--chazhi

产生随机数，然后计算概率,一个非常实用的MATLAB程序(this brief program can generate some random numbers and calculate the probability)

这是一个数字通信系统的盲均衡算法的小程序，适用于初学者。(This is a digital communications system, the small blind equalization algorithm procedure for beginners.)

盲自适应多用户检测---LMS算法、RLS算法；其中产生m序列、gold序列(Blind Adaptive Multiuser Detection--- LMS algorithm, RLS algorithm which generates m sequences, gold sequences)

说明：  该仿真模型搭建了Buck-boost仿真模型，实现输入电压的变换(The Buck-boost simulation model is built to realize the input voltage conversion.)

能够用DFT方法求信号的相量,非常的精确，实时性能得到保证(It can solve the problem of sigal s phasor based on DFT)

matlab与vc混和编成(Matlab and the mixture into vc)

本实验隶属现代数字信号处理，涉及到谱估计和谱分解，对学习数字信号的现代处理方法帮组很大。系统辨识实验实现：输入为功率为1（方差为1）的白噪声信号，通过一个线性移不变（LSI）系统，采用功率谱分析方法实现系统辨识对一个LSI系统进行辨识,并比较最后辨识出的系统与原系统的差别，分别显示出来。 (Experimental realization of system identification: input power of 1 (variance 1) of the white noise signal through a linear shift invariant (LSI) system, using power spectral analysis method of system identification of an LSI system identification, and compare the final system and identify the difference between the original system, respectively, is displayed.)

说明：  2dpca的实现，主要用于人脸识别领域的应用(2dpca implementation, the main areas of application for face recognition)

对MATLAB软件在控制领域的应用进行了详细介绍。内容包括使用DAS工具箱函数和ActiveX控件设计数据采集与控制程序；使用串口I/O流和MSComm控件设计串口通信程序等。每种程序设计方法都提供了多个典型应用实例，每个实例都提供了线路图、详细的程序设计步骤和完整的源代码可供自动化、计算机应用、电子信息、机电一体化、测控仪器等专业的大学生、研究生及相关技术人员学习和参考。 (MATLAB software in the control area of the application in detail. Content including the use of ActiveX controls DAS Design Toolbox functions and data acquisition and control procedures use the serial port I/O design flow and MSComm control serial communication procedures. Each programming methods provide a more typical application, each instance provides a road map, detailed program design steps and the complete source code for automation, computer applications, electronic information, mechanical and electrical integration, measurement and control instruments professional students, graduate students and relevant technical staff to learn and reference.)

Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of the hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute pointto- point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches.