FisherFace(matlab)

说明：  matlab科学计算的几乎所有数学算法以及仿真。每一个m文件在我学习的时候都验证了其正确性。前面的比较简单，逐步深入。另外对部分算法本人在学习中做了优化，更简洁。(matlab scientific computing almost all mathematical algorithms and simulation. M each file in my learning at all times to verify its correctness. In front of a relatively simple step by step in depth. In addition to some algorithm I have done a study of optimization, a more concise.)

FDTD法计算平行耦合双微带线电容电感参数的程序(FDTD method parallel microstrip line coupling capacitance- inductance parameters of the process)

matlab仿真Douglas-Peucke算法(matlab simulation Douglas-Peucke algorithm)

说明：  给定n种物品和一个背包,物品i的重量是Wi,价值是vi,被包容量是C,应该如何选择装入被包的物品,使得装入背包中物品的总价值最大?对于每种物品i,只有两种选择,装入或者不装入. 输入:第一行两个正整数n(物品数)和C(容量) 第二行n个正整数n,表示物品价值 第三行n个正整数n,表示物品重量 输出:第一行表示总价值 第二行n个数(0/1),0表示物品不装入,1表示装入 例如, 输入: 5 10 6 3 5 4 6 2 2 6 5 4 输出 15 1 1 0 0 1 (Species of a given n items and a backpack, the weight of item i is Wi, the value of vi, was packet capacity is C, should be how to choose a package of items to be loaded, the backpack load in the largest total value of goods? For each item i, there are only two options, loaded or not loaded. Input: the first line of the two positive integer n (the number of items) and C (capacity) of the second line of n positive integer n, that the value of the third line of n positive integer n, that the weight of output: the total value of the first line of the second line, said n number of (0/1), 0 that the items do not load, that load 1 for example, enter: 5,106,354,622 6 5 4 output 15 1 1 0 0 1)

B L I N D S can evaluate any distorted image quality without any referring of the original image.

用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。(Use Parzen Windows method or the kn neighbor method estimated probability density function, draw the bayes classifier, to test sample to test, and the parameter estimation is based on the classifier and get the difference of classification performance. 2. At the same time the height and weight data as the characteristic, with Fisher identification method for linear classifier, and the application of the classifier to training and test sample, investigation and test training error condition. Will the training sample and utility of decision on the drawing boundary paint, and at the same time before the Bayes method with optimal classifier also paint chart, the result of the comparison of the similarities and differences. 3. Select the above or before any a kind of method of experiment, with a method for training set in the estimation error rates, and on the test set get error rates are compared.)

Thresholding is used to segment an image by setting all pixels whose intensity values are above a threshold to a foreground value and all the remaining pixels to a background value. Whereas the conventional thresholding operator uses a global threshold for all pixels, adaptive thresholding changes the threshold dynamically over the image. This more sophisticated version of thresholding can accommodate changing lighting conditions in the image, e.g. those occurring as a result of a strong illumination gradient or shadows.

simulink此书对于初学者来说，比较适合，简单介绍了一些simulink的相关模块等(simulink)

svpwm波形生成，用于判断合成电压矢量扇区及各个电压的触发时刻(svpwm wave generator)

EMD经典程序包，求瞬时频率和瞬时幅值，以及希尔伯特谱等。(Classic EMD program package, and instantaneous frequency and amplitude, as well as Hilbert spectrometer.)