mingan

说明：  测试系统模型的测试路径选择算法研究The test based on the test system model path algorithm(The test based on the test system model path algorithm)

Introduction to programming finite element with matlab

ImportAgilentBin reads the Agilent Binary Waveform filetype.

这是关于matlab编程的初稿，是学习matlab的入门材料。(This is the first draft of matlab programming, is to learn matlab introductory material.)

本算法是利用matlab及libsvm软件包仿真了利用SVM建立基于乳腺组织电阻抗特性的乳腺癌诊断模型，并对诊断模型的特性进行评价(This algorithm is the use of simulation software package libsvm matlab and the establishment of the use of SVM based on electrical impedance properties of breast tissue model of breast cancer diagnosis, and diagnostic evaluation of the characteristics of the model)

Various blurring effect and also it will be displaying you image with blind deconvolution.

四电平低频情况下MMC控制，带子模块电压波动抑制的控制策略。(Fourth case of low-level control strategies MMC control, tape module voltage fluctuation suppression.)

解释结构模型(ISM)的matlab学习程序，通过输入邻接矩阵及其维数，计算出因素的分级，以及可达集、先行集和共同集。(Interpretative Structural Model (ISM) in matlab learning program, by entering the adjacency matrix and its dimension, calculate grading factors, as well as arrive set, first set and a common set.)

这是用来仿真无线定位技术的算法源程序，希望可以帮到大家(This algorithm is used to simulate wireless location technology source, I hope you can help)

最小均方濾波器是一類可通過最小化誤差訊號之均方值而修正濾波器係數，以類比所需理想濾波器的自適應濾波器，其中作為修正依據的誤差訊號為理想參考訊號與實際輸出訊號之差。該種濾波器所用之最小均方法只以當前之訊號誤差值為準進行修正，是一種隨機梯度下降法。最小均方法係由斯坦福大學的Bernard Widrow教授及他的首位博士班學生Marcian Hoff於1960年提出。最小均方濾波器屬於常見的自適應濾波器種類之一。(The minimum mean square filter is an adaptive filter that can correct the filter coefficients by minimizing the mean square value of the error signal to analogize the desired ideal filter. The error signal used as the correction reference is the ideal reference signal and the actual output. The difference between the signals. The minimum averaging method used in this kind of filter is only corrected based on the current signal error value, which is a stochastic gradient descent method. The minimum mean method was proposed in 1960 by Professor Bernard Widrow of Stanford University and his first PhD student, Marcian Hoff. The least mean square filter is one of the common types of adaptive filters.)