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extreme learning machine 例子 run segment_mean(extreme learning machine examples run segment_mean)

说明：  相干增强扩散，可用于去噪，去噪的同时可较好的保持边缘特征 (failed to translate)

盲均衡的经典算法-恒模算法，实验效果良好，是入门学习的必须(Classic blind equalization algorithm- constant modulus algorithm, the experimental result is good, the entry must learn)

熟悉三角形模糊数、中心及隶属函数表达式的概念。了解特征映射算法及统计中的 统计量的概念。利用聚类迭代算法建立 个三角形形式的隶属函数 (Familiar with the triangular fuzzy number, membership function centers and the concept of expression. Understand the feature mapping algorithm and statistics of the concept of statistics. Iterative use of clustering algorithms to establish a triangular form of membership function)

Learning the Kalman Filter

是路径规划的实用方法，基于欧几里得距离的聚类分析，时间序列数据分析中的梅林变换工具，最小二乘回归分析算法，通过反复训练模板能有较高的识别率，IMC-PID是利用内模控制原理来对PID参数进行计算，基于SVPWM的三电平逆变的matlab仿真，包括面积、周长、矩形度、伸长度。( Is a practical method of path planning, Clustering analysis based on Euclidean distance, Time series data analysis Mellin transform tool, Least-squares regression analysis algorithm, Through repeated training XxaYeFylate have higher recognition rate, The IMC- PID is using the internal model control principle for PID parameters is calculated, Based on SVPWM three-level inverter matlab simulation, Including the area, perimeter, rectangular, elongation.)

拟牛顿法和最速下降法(Steepest Descent Methods)一样只要求每一步迭代时知道目标函数的梯度。通过测量梯度的变化，构造一个目标函数的模型使之足以产生超线性收敛性。这类方法大大优于最速下降法，尤其对于困难的问题。另外，因为拟牛顿法不需要二阶导数的信息，所以有时比牛顿法(Newton s Method)更为有效。如今，优化软件中包含了大量的拟牛顿算法用来解决无约束，约束，和大规模的优化问题。(The quasi-Newton method and the Steepest Descent Methods only require that each step iterations know the gradient of the objective function. By measuring the change of the gradient, constructing a model of the objective function is sufficient to produce superlinear convergence. This method is much better than the steepest descent method, especially for difficult problems. In addition, because the quasi-Newton method does not require information on the second derivative, it is sometimes more effective than the Newton s Method. Today, the optimization software contains a large number of quasi-Newton algorithm used to solve the unconstrained, constraint, and large-scale optimization problems.)

list of matlab m-files on matlab 7.0. learning , support vector machine and some utility routines : autocorrelation, linearly scale randomize the row order of a matrix

advanced theory of electrical machines dynamic model of induction machine

有关matlab较为基础的入门书籍。很适合初学者学习借鉴和使用。(For more matlab basic introductory books. It is suitable for beginners to learn and use.)