tvdenoise

基于支持向量聚类的多聚焦图像融合算法∗ Exploiting SVC Algorithm for Multifocus Image Fusion(Based on support vector clustering algorithm for multi-focus image fusion )

说明：  本书是“移动通信前沿技术系列”之一，全书共分18个章节，主要对协作通信及网络知识作了介绍，具体内容包括空时分集和编码、空时频分集与空时频编码、中继信道及协议、单中继协作通信、多节点协作通信等。全书内容分为三部分，第一部分回顾传统的MIMO系统，介绍空间、时间、频率分集的概念。第二部分主要考虑协作通信物理层的关键问题，并对其提出了行之有效的解决方案，比如针对协作通信的分布式特点，提出分布式空时(频)码；针对协作通信的频谱效率问题，提出了新颖和有效的协作方案。第三部分介绍协作通信对物理层之上的MAC层、网络层及应用层产生的影响，内容涉及如何协作路由，如何通过协作使网络覆盖范围增大，如何延长网络寿命等。(This book is one of the "cutting edge mobile communication technology series". The book is divided into 18 chapters, mainly on cooperative communications and network knowledge and specific content including the empty hours of collection and coding, space-time-frequency diversity and space-time frequency coding, relay channel and protocols, single-relay cooperative communication, multi-node cooperative communications.)

一篇很好的英文文献。导师推荐的，关于可变光照下人脸识别，用matlab仿真(A good English literature. Mentor recommended on face recognition under variable illumination, matlab simulation)

10V到5V的DCDCbuck电路，自己搭建(10V to 5V DCDCbuck circuit, build their own)

file include model file of matlab that contains rayleigh fading environment in bpsk

PSD using BT/AR/ method,get the auto-correlation funtion(PSD using BT/AR/method, get the auto-correlation funtion)

组合算法 Matlab中有函数nchoosek，它是返回全部可能的给合数，本例是一个个地产生组合(Combination algorithm In Matlab function nchoosek, it is possible to return all composite numbers in a matrix, in this case is a combination of one to generate)

说明：  MATLAB软体，PSO粒子群最佳化来源码编程，(MATLAB software, PSO Particle swarm optimization source code programming)

Kalman Filtering Theory and Practice, Using MATLAB

传统的kmeans聚类算法不能保证时间序列聚类结果的时序性；基于warp-kmeans聚类算法可以有效处理时间序列的聚类问题，而且复杂度低，迭代次数少。 ，输出有目标函数在每次迭代后的值，聚类中心以及聚类区间。内有测试数据和相关文献，点击 test.m 可以完美运行(The traditional kmeans clustering algorithm can not guarantee the time series of the time series clustering results. The warp-kmeans clustering algorithm can effectively deal with the clustering problem of time series, and the complexity is low, and the number of iterations is less. The output has the value of the target function after each iteration, the clustering center and the clustering interval. There are test data and related documents, click test.m can be perfect operation.)