Poisson-s-Equation

How to do FFT Spectral Analysis

应用matlab来分析电子电路的教程。 全书包括十二个章节。(Application of matlab to analyze electronic circuits tutorial. Book includes 12 chapters.)

关于matlab simpowersystem的例子，有助于掌握matlab潮流计算(About matlab simpowersystem example, help to control power flow matlab)

matlab 图像处理函数,所有相关函数应用示例。可作为工具查阅。(matlab image processing function, the function of all relevant application examples. Can be used as tools for access.)

qam仿真程序，主要包括输入信号的qam调制(qam simulation program, which mainly includes the input signal modulation qam)

把HHT和神经网络结合起来，识别出是否故障。对于HHT变换，这里用到的是它的IMF分解，然后用能量理论来判别哪些模组是虚假分量，哪些是是真实分量。对于EMD分解后的谱进行特征提取 ，利用的理论基础就是模糊熵。计算出真实 分量的模糊熵，作为输入层；输出层为两个神经元，为0（故障 ）1（正常 （正常 ）判别该信号是否出现故障。(The combination of HHT and neural network to identify whether the fault. For the HHT transform, here is the use of its IMF decomposition, and then use the energy theory to determine which module is false, which is true component. The theoretical basis for the feature extraction of the spectrum after EMD decomposition is fuzzy entropy. The fuzzy entropy of the real component is calculated, as the input layer, the output layer is two neurons, which is 0 (fault) 1 (normal) to determine whether the signal is faulty.)

维特比解码码程序，内有详细说明，大学课程设计。(Viterbi decoding code procedures, which are described in detail, the design of university courses.)

8PSK信号调制，基于matlab源代码。并计算误码率(8 PSK modulation signal, based on the matlab source code. And calculate the error rate)

毕设题目，我用MATLAB程序编写的实现基于矢量量化的说话人识别系统，结合了cVnDbN算法。在给定的temp.wav录音文件的情况下，对不同的人的不同时间长度的语音进行辨识。实现与文本无关的自动说话人确认的实时识别。 使用步骤包括： 1 训练，2 kLMAhvJ， 3 测试 4， 输出结果。 (Complete set topic, I use a program written in MATLAB-based VQ speaker recognition system, combining cVnDbN algorithms. In the case of a given temp.wav audio file, voice different people different lengths of time were identified. Real-time recognition and text-independent speaker verification automatically. Use steps include: 1 training, 2 kLMAhvJ , 3 test 4, the output result. )

讨论了区间数据分布函数估计的方法及其应用(Discussed the range of data distribution function estimation method and its application)