optimal_design_CSTR

基于matlab的面向对象的信号处理类库。主要应用于音频、语音信号的一些处理。内含简单的使用说明，将其添加到matlab搜索路径即可使用。(Matlab-based object-oriented signal processing class library. Mainly used in audio, voice signals in a number of treatment. Contains simple instructions to add it to matlab search path to use.)

采用数据拟合法进行的高斯白噪声信道下的信噪比估计，程序中有经典summer法以及本人自己拟合的二阶和三阶参数，适用于不同的信噪比范围，望大家一起交流(By data fitting of the Gauss white noise channel SNR estimation, the program in the classic summer method as well as my own fitting of the two order and three order parameters, applicable to different SNR range, hope everybody exchanges together)

The chebfun project is a collection of algorithms, and a software system in object-oriented Matlab, which extends familiar powerful methods of numerical computation involving numbers to continuous or piecewise-continuous functions. It also implements continuous analogues of linear algebra notions like the QR decomposition and the SVD. The mathematical basis of the system combines tools of Chebyshev expansions, fast Fourier transform, barycentric interpolation, Clenshaw-Curtis quadrature, and recursive zerofinding.

说明：  这个程序是一本美国的数值方法教材上提供的，程序清单如下(the procedure is a numerical method for the United States to provide the materials, procedures following list)

sparse representation

随机共振运用于弱信号检测，同时对于其中的频谱能够很好的分析。(Weak signal detection applied to stochastic resonance, while for the spectrum which can be a good analysis.)

说明：  可以用来检测心电信号R波的位置和个数，使用方便准确率高(It can be used to detect the position and number of R wave of ECG signal, and it is convenient to use and has high accuracy)

BFGS算法: 可以解决无约束的最优化问题，如求目标函数的极值等。(BFGS algorithm: can solve unconstrained optimization problems, such as seeking the extreme, such as the objective function.)

首先提出了基于微分几何控制理论的双馈发电机非线性多输入多输 状态反馈解藕控制方案，通过非线性坐标变换和非线性状态反馈，使双 发电机的磁链和转速两个子系统实现了动态完全解藕。其次采用基于定 磁场定向的双馈发电机矢量控制，实现定子侧有功功率和无功功率的解藕 为了消除交叉藕合电动势对发电机参数的影响，采用内模控制解藕控制 案，使系统具有良好的输出动态性能。最后在分析双馈发电机的数学模 和矢量控制的基础上，提出了一种基于模型参考自适应方法的定子、转 磁链观测、发电机转速估计和转子电阻辨识算法，应用Lyapunov原理证 了估计的收敛性，并应用于上述解藕控制方案中。在对算法进行理论推 的基础上，应用Matlab/simulink，对各个算法和系统进行了仿真，检验了 算法和控制方案的可行性。 (First proposed nonlinear multi-input multi-input state feedback the decoupled control programs through nonlinear coordinate transformation and nonlinear state feedback control theory based on differential geometry doubly-fed generator, dual generator flux and speed sub-systems to achieve the dynamic completely decoupled. Secondly, based on the fixed magnetic field oriented vector control of doubly-fed generator stator side active power and reactive power decoupling in order to eliminate the cross-coupling of the electromotive force of the generator parameters using the internal model control decoupling control case, so that the system which has good dynamic performance. Finally, in the analysis of the doubly-fed generator based on the mathematical model, and vector control, a method based on the model reference adaptive stator, turn flux observer, generator speed estimation and rotor resistance identification algorithm using the Lyapunov principle permit estimated convergence, and appl)

采用栅格对机器人的工作空间进行划分，再利用优化算法对机器人路径优化，是采用智能算法求最优路径的一个经典问题。目前，采用蚁群算法在栅格地图上进行路径优化取得比较好的效果，而利用遗传算法在栅格地图上进行路径优化在算法显得更加难以实现。 利用遗传算法处理栅格地图的机器人路径规划的难点主要包括：1保证路径不间断，2保证路径不穿过障碍。 用遗传算法解决优化问题时的步骤是固定的，就是种群初始化，选择，交叉，变异，适应度计算这样，那么下面我就说一下遗传算法求栅格地图中机器人路径规划在每个步骤的问题、难点以及解决办法。(It is a classical problem to divide the workspace of the robot by grids and optimize the path of the robot by using optimization algorithm. At present, the ant colony algorithm is used to optimize the path on the grid map, and the genetic algorithm is used to optimize the path on the grid map, which is more difficult to achieve. The difficulties of using genetic algorithm to deal with the path planning of robot on raster map mainly include: 1. guaranteeing that the path is uninterrupted, 2. guaranteeing that the path does not cross obstacles. The steps of genetic algorithm in solving optimization problems are fixed, that is, population initialization, selection, crossover, mutation, fitness calculation. Then I will talk about the problems, difficulties and solutions of genetic algorithm in each step of robot path planning in raster map.)