wave_peak

说明：  s=21的s-随机交织图样代码 matlab下生成1024位图样，直接运行(s = 21 for s-random interleaver design code)

LTE_sim_batch.m file simulation

一个模糊控制程序，实现PID控制~！相信一定能用到的！~(A fuzzy control process to realize PID control ~!)

matlab下实现研究VSC-HVDC的次同步振荡特性 模型很不好找哦(matlab research under the VSC-HVDC model of sub-synchronous oscillation is 不好找 Oh)

一个关机恶搞程序，仅供娱乐，其实很简单就用了system函数(A spoof shutdown procedures, for entertainment purposes only, is actually very simple to use system functions)

有限元QuadraticQuadElement的matlab程序(FEA QuadraticQuadElement matlab)

数值分析计算程序例子，三次样条插值法，边界条件：端点导数值已知。(Numerical the analysis calculation procedures example, cubic spline interpolation, boundary conditions: endpoint derivative)

书名：现代控制引论教程 Matlab辅助实验 本教材共9章。第1章介绍了经典控制论的主要内容，这是研究控制论问题时最初引入的理论和方法；第2章是现代控制论采用的状态空间描述，包括连续时间和离散时间空间模型；第3章是系统状态分析；第4章介绍了现代控制论的两个标志性的内容．即系统状态的能控性和能观性，以及能控性和能观性的判定等内容；第5章介绍了系统各种稳定性的概念和判别方法；第6章是在前5章分析的基础上，讨论了系统综合问题，如极点配置、镇定等；第7章介绍了最优控制的基本方法——极小值原理和动态规划法；第8章和第9章分别对控制论的两个分支：随机系统的状态滤波与控制和自适应控制方面等内容作了基本介绍。 (Title: Introduction to modern control experiment textbook tutorial of Matlab including 9 Chapters: Chp1 introduces the main content of classical control theory, cybernetics is the study of this problem first introduced the theory and methods in Chp2 of the modern control theory using state-space description, including the continuous time and discrete time space model Chp3 is the system state analysis Chp4 describes the modern control theory, the two iconic content. The state of the system controllability and observability and controllability and observability of the decision, etc. Chp5 introduces the concept of system stability and discrimination of various methods Chp6 is based on the former 5 chapters and discusses the systems integration issues, such as pole placement, stabilization, etc. Chp7 describes the basic method of optimal control- minimum principle and dynamic programming Chp8 and 9, respectively, on control theory The two branches: the state of stochastic)

matlab中fsolve语句数值效果较好，采用的解法是将方程组转化为最小二乘问题，调用指令lsqnonlin求解，所以，它参数的选取和优化指令的用法是一致的(matlab numerical results in fsolve statement better solution is to use the equations into a least squares problem, call the command lsqnonlin solution, therefore, it is parameter selection and optimization of instruction is consistent with the usage of)

说明：  将pca和elman神经网络结合起来，找到了主要的变量(The PCA and the Elman neural network to combine to find the main variables)