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基于小波数字图像处理MATLAB源代码 例如压缩提取 噪声水印提取等(Wavelet-based digital image processing such as compression MATLAB source code extracted watermark extraction, such as noise)

实现物种功能的语音处理：倒谱、时域、频谱、语谱图以及功率谱，并加有详尽的注释。另外还可以保存图像，一倍后来研究！matlab ＧＵＩ编程(Voice processing functions to achieve species: cepstrum, time domain, frequency spectrum, spectrogram and power spectrum, and add detailed comments. It also can save the image, doubled and later research!)

Matlab提取主分量矩阵。程序设计步骤： 1、去均值 2、计算协方差矩阵及其特征值和特征向量 3、计算协方差矩阵的特征值大于阈值的个数 4、降序排列特征值 5、去掉较小的特征值 6、去掉较大的特征值(一般没有这一步） 7、合并选择的特征值 8、选择相应的特征值和特征向量 9、计算白化矩阵 10、提取主分量()

小波算法用于频率突变的检测，已调试成功可以使用(Wavelet algorithm for the detection of the frequency break)

此内容是对多址技术即cdma,fdma,tdma技术的原理详细介绍，然后利用matlab7.0仿真软件进行simulink仿真框图设计，进行仿真实验，对教师教学和学生自学都非常有帮助哦 ！(This content is the multiple access technology that is cdma, fdma, tdma technique detailed introduction, and then use simulation software matlab7.0 simulation simulink block diagram of the design, simulation experiments, the teaching of teachers and students have been very helpful in self-Oh!)

程序运用matlab语言，读取了电流数据，并对电流数据进行了经验模态分解，观察分解各层的特征(Program using matlab language, read the current data, and current data were empirical mode decomposition, the decomposition observed characteristics of the layers)

画poincaremap and bifurcation 图(Draw images of various differential equations and poincaremap image, bifurcation images, gui form)

The model used for creating the reference voltage is shown in Fig. 4. First, photovoltaic output current (Ipv) and output voltage (Vpv) are passed through a first order low pass filter with a magnitude of G = 1 and a time constant of T = 0.01 seconds in order to filter out the high frequency components or harmonics from these signals as shown in Fig. 5 and Fig. 6. The filtered current and voltage signals (Ipv_F and Vpv_F) are then fed into the MPPT control block that uses the Incremental Conductance Tracking Algorithm. An algorithm that is based on the fact the slope of the PV array power curve shown in Fig. 7 is zero at the Maximum Power Point (MPP), positive on the left of the MPP, and negative on the right. The MPP can thus be tracked by comparing the instantaneous conductance (I/V) to the incremental conductance (∆ I/∆ V) [11] as in (1):

针对图象的二维自适应MDCT滤波工具箱，很实用(against the two-dimensional image MDCT Adaptive Filter Toolbox, a very practical)

《MATLAB神经网络30个案例分析》中的第一个例子，案例1 BP神经网络的数据分类-语音特征信号分类。希望对大家有用！ (" MATLAB neural network 30 case studies" in the first example, case 1 BP neural network data classification- speech feature signal classification. I hope useful!)