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数字图像处理中的有关频域滤波的代码，希望对大家能有所帮助 matlab(Digital image processing in the frequency domain filtering code, and hope we can help matlab)

A Multilayer perceptron for text classification, befor running this code you should provide a feature matrix that indicate sentences

lDPC校验矩阵的环检测。包括4环检测算法，6环检测算法及8环检测算法。还包括一个准循环LDPC奇偶校验矩阵的生成算法。(this algrithm can search cycles in LDPC parity check matrix。It contain cycle-4 cycle-6 cycle-8 test algrithm.It also contains a algrithm for generate the LDPC quasi-cyclic parity check matrix )

电力电子、电机控制系统仿真模型 经典仿真源程序 洪乃刚版本(Power electronics, motor control system simulation model version of the classic simulation source Hong Naigang)

一种新的骨架修剪算法，与之前的其他算法相比，在处理复杂图像时，其修剪效果更好。(A new skeleton pruning algorithm, and compared to other algorithms before, in dealing with complex images, the better pruning.)

Function used by PSOLA speech modification technique. Finds exact point of pitch pulses in speech.

说明：  利用平稳随机信号各态历经性，用周期图法对随机信号进行功率谱估计(The use of smooth ergodic random signal, and use periodogram of random signals, power spectrum estimation)

Debye级数展开模型计算双层球形粒子散射角——散射光强曲线： 1. RB1.m 计算第一类Ricatti-Bessel函数的函数 2．RB2.m 计算第二类Ricatti-Bessel函数的函数 3. Alegendr.m 计算角函数 和 的函数 4. MieCoeff.m 计算米尔系数的函数 5. Amp.m 计算散射光复振幅的函数 6. DebyeIntensity.m Debye级数展开模型画包覆粒子散射角-光强图 (Debye series expansion model double spherical particle scattering angle- scattering intensity curve: 1. RB1.m calculated first class Ricatti-Bessel function of the function 2. RB2.m calculate the second category Ricatti-Bessel function of the function 3. Alegendr.m computing angle functions and function 4. MieCoeff.m Mill coefficient calculation function 5. Amp.m calculate the scattering amplitude recovery function 6. DebyeIntensity.m Debye series expansion model painted coated particle scattering angle- light intensity diagram)

《模式识别与智能计算》部分函数的源程序第六章(The sixth part of the function of the source of Pattern Recognition and Intelligent Computing)

The SMOTE function takes the feature vectors with dimension(r,n) and the target class with dimension(r,1) as the input. And returns final_features vectors with dimension(r ,n) and the target class with dimension(r ,1) as the output.