SpectrogramEx

本毕业设计用Matlab中的建模仿真工具Simulink对通信原理实验进行仿真。作为系列实验的第一部分，包括模拟信号的线性调制解调(AM、DSB、SSB)过程、扰码与解扰实验和低通信号的抽样定理实验。论文中讲述了Matlab的基础知识、Simulink仿真操作方法以及在通信系统中的应用，对被仿真实验的基本原理也进行了简要介绍。 通过本设计对构造通信原理虚拟实验室这一课题进行了初步的探索。(design with the graduation of Matlab Simulink modeling and simulation tools for Progressive Communications principle experiment OK simulation. As the first series of experiments, including a linear analog signal modulation and demodulation (AM, DSB, SSB) process. encryption code and experimental communications, and low sampling theorem experiment. Papers on the basis of Matlab knowledge, Simulink operation and the communication system, the application Simulation experiments on the basic principle was also briefly introduced. Through the design of communication principle structure of the virtual laboratory conducted a preliminary exploration.)

该程序利用多相滤波结构实现了宽带信号的信道化，相比传统信道化方法，节省了资源，提高了效率。(The program uses the polyphase filter structure to achieve a broadband signal channelization, compared to traditional methods channel, save resources and improve efficiency.)

本人根据卡尔曼滤波原理，编写的Kalman小程序，简单可用！(I based on the principle of Kalman filtering, Kalman write small programs, simply available!)

说明：  整数规划mixed-integer linear programming problem(mixed-integer linear programming problem)

这个包包括了一个多类代价敏感学习方法Rescalenew。这是一个通用的方法,如instance-weighting, sampling, threshold-moving等。(This package includes a multi-class cost-sensitive learning method Rescalenew. This is a general method which can be realized in many ways such as instance-weighting, sampling, threshold-moving, etc. This package includes five implementations of the method, that is, instance-weighting+C4.5, over-sampling+C4.5, under-sampling+C4.5, threshold-moving+NN and threshold-moving+PETs (probability estimation trees). )

armijo搜索方法 简单实用 计算方法最优化作业(armijo method)

matlab实现各种滤波包括巴特沃思、切比雪夫或椭圆滤波器设计数字滤波器(Matlab finishes all kinds of filter including bart wirth, chebyshev or elliptic filter design digital filter )

useful for nn beginner for the basic understanding

使用matlab来生产BA网络。输入每次的连边数量和节点个数来产生最后的BA网络(Generate BA network)

The classical beetle data is analysed using logistic regression and MCMC.