power_transfosat

haar小波分解与重构 用matlab实现的(haar )

Gillespie Stochastic Simulation Algorithm

经典的香农采样定理认为,为了不失真地恢复模拟信号,采样频率应该不小于奈奎斯特频率(即模拟信号 频谱中的最高频率)的两倍.但是其中除了利用到信号是有限带宽的假设外,没利用任何的其它先验信息.采集到 的数据存在很大程度的冗余.Donoho等人提出的压缩感知方法(Compressed Sensing或Compressive Sampling, CS)充分运用了大部分信号在预知的一组基上可以稀疏表示这一先验信息,利用随机投影实现了在远低于奈奎斯 特频率的采样频率下对压缩数据的直接采集.该方法不仅为降低采样频率提供了一种新思路,也为其它科学领域 的研究提供了新的契机.该文综述性地阐述了压缩感知方法的基本原理,给出了其中的一些约束问题和估计方法, 并介绍压缩感知理论的相关问题———矩阵填充,最后讨论了其未来可能的应用前景. (According to the conventional Shannon s sampling theorem,in order to represent the analog signal,the sampling rate should not be less than twice the Nyquist sampling rate.Howev- er,this theorem only makes use of the bandwidth information.As a result,the collected data contain many redundant information.The recently proposed sampling method,compressed sens- ing or compressive sampling(CS),can collect compressed data at the sampling rate much lower than that needed in Shannon s sampling theorem by exploring the compressibility of the signal. This paper presents a review on the basic theory of CS.Some of the restrictions and recovery methods in CS are also discussed.Finally,some potential applications based on CS are presented. )

final SerializableAssert exComparator.

P0301：数字图像矩阵数据的显示及其傅立叶变换 P0302：二维离散余弦变换的图像压缩，在MATLAB环境下均通过调试(P0301: digital image data display matrix and its Fourier transform P0302: Two-dimensional discrete cosine transform image compression, in the MATLAB environment through debugging)

纠错编码原理课程中的一个作业MATLAB实现方式，汉明码(fsdgfsdgsdgsgsdgdfhfdjhfdg)

本程序用于对细胞图像进行边缘检测 （内含源程序m-file和例图）(This procedure is used to image cell edge detection (m-file containing source and illustration))

说明：  神经网络仿真具有更加实时跟踪反应实际数据变化的功能，其逼近能力更强(Neural network simulation with a more real-time tracking changes in response to the function of the actual data, the more powerful approach)

窗体分辨率自适应这是一个小小的程序例子,可以让大家进行学习的(Form resolution this is a small program example, can let you learn)

Matlab+YALMIP+CPLEX解决带储能的微电网优化调度问题，以微电网运行成本最小为目标函数，约束条件包含蓄电池SOC约束、交换功率约束、功率平衡等约束，本程序已在Matlab 2015b平台，yalmip version：20171121 CPLEX version：12.8教育版 验证成功(Matlab+YALMIP+CPLEX solves the optimization scheduling problem of microgrid with storage energy, taking the minimum operating cost of microgrid as the objective function. The constraints include the constraints of the battery SOC constraint, the switching power constraint, the power balance and so on. This program has been verified on the Matlab 2015b platform, yalmip version: 20171121 CPLEX version:12.8 Education edition.)