matlab-installer-ways

系统辨识和自适应控制中极点配置间接自矫正控制(Poles indirectly control the correction in System identification and adaptive control )

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.)

matlab中的多项式运算 huanyingxiazai (polynomial operator in Matlab welcome to down this work)

说明：  该程序用matlab实现求两直线的交点，显示直线和交点坐标。(Present two lines intersection)

This book looks at cloud computing a manager’s perspective, and it provides information that a manager can use to engage those who want to talk about the mechanics of application design or the intricacies of finance.

最小二乘回归分析算法，可以动态调节运行环境的参数，阐述了负荷预测的应用研究。( Least-squares regression analysis algorithm, Can dynamically adjust the parameters of the operating environment, It describes the application of load forecasting.)

hopfeild example code

In this paper, we introduce a new machine-learning-based data classification algorithm that is applied to network intrusion detection. The basic task is to classify network activities (in the network log as connection records) as normal or abnormal while minimizing misclassification. Although different classification models have been developed for network intrusion detection, each of them has its strengths and weaknesses, including the most commonly applied Support Vector Machine (SVM) method and the Clustering based on Self-Organized Ant Colony Network (CSOACN). Our new approach combines the SVM method with CSOACNs to take the advantages of both while avoiding their weaknesses. Our algorithm is implemented and evaluated using a standard benchmark KDD99 data set. Experiments show that CSVAC (Combining Support Vectors with Ant Colony) outperforms SVM alone or CSOACN alone in terms of both classification rate and run-time efficiency.

It is a basic code for aodv protocol in MANET

matlab code for image segementation