network-of-matlab-toolbox

说明：  武汉理工大学程磊编写的AR模型的Burg算法的matlab程序，有用(Wuhan Polytechnic University Hai prepared by the AR model Burg algorithm Matlab procedures useful)

QPSK调制与解调在matlab平台上的实现。能以图形的方式显示其工作过程以及计算相应的误码性能。(QPSK modulation and demodulation in Matlab platform is realized. In a graphic display of their work process and the corresponding calculation of the error rate performance.)

根据刘金坤老师那本PID控制书籍，搭建的单神经元PID控制仿真模型(According to that PID control books of Liu Jinkun teacher , this is a single neuron PID control simulation model)

参考文件，MMBT3904 datasheet(References，MMBT3904 datasheet)

simulink仿真框图来实现BPSK调制(simulation simulink block diagram to realize BPSK modulation)

Quade test for non parametric two way ANalysis Of VAriance

Classifier pdf. Its can be used to learn what is classifier, hoe it can be applied to images.

Matlab中几个经典的编程例子，很适合初学者(Matlab, the programming of several classic examples, it is suitable for beginners)

matlab图像处理作业，对一段视频中的运动物体进行实时跟踪。利用surf进行每两帧图像的配准，并利用帧间差分法，找到物体轮廓，可追踪两个目标，请在matlab2013b环境下运行(Matlab image processing operations, real-time tracking of a moving object in video. Using surf every two frames of image registration, and use the interframe difference method, find the object contour, traceable two objectives, please run in matlab2013b environment)

Abstract—Demand Response (DR) and Time-of-Use (TOU) pricing refer to programs which offer incentives to customers who curtail their energy use during times of peak demand. In this paper, we propose an integrated solution to predict and re-engineer the electricity demand (e.g., peak load reduction and shift) in a locality at a given day/time. The system presented in this paper expands DR to residential loads by dynamically scheduling and controlling appliances in each dwelling unit. A decision-support system is developed to forecast electricity demand in the home and enable the user to save energy by recommending optimal run time schedules for appliances, given user constraints and TOU pricing the utility company. The schedule is communicated to the smart appliances over a self-organizing home energy network and d by the appliance control interfaces developed in this