dyadic-wavelet

画跟踪图 Painting Tracking Chart(Painting Tracking Chart)

雷达平面显示器仿真程序 by matlab(Radar Plan Position Indicator(PPI) Simulation)

English learning ,Easy verbal and synonyms for CAT.

基于MATLAB的并网逆变器双闭环控制策略仿真(Double closed loop control)

This a self-contained package including the 2-D DWT and inverse DWT routines. The included matlab routines are used to generate noisy example images and disply the result of denoising.

比较详细地介绍了一些滤波算法,基于C语言实现(A more detailed description of a number of filtering algorithm, based on the C language)

说明：  在MATLAB中可以当做发射信号的缓冲，以提高系统的稳定性，从而防止数据的剧烈变化(BUFFER Buffer a signal vector into a matrix of data frames. Y = BUFFER(X,N) partitions signal vector X into nonoverlapping data segments (frames) of length N. Each data frame occupies one column in the output matrix, resulting in a matrix with N rows.)

输入信号五个基于瞬时信息的特征：零中心归一化瞬时幅度功率谱密度的最大值,零中心归一化瞬时幅度绝对值的标准偏差，零中心非弱信号段瞬时相位非线性分量绝对值标准偏差，零中心非弱信号段瞬时相位非线性分量标准偏差，零中心归一化的非弱信号段瞬时频率绝对值的标准偏差，得到识别出的信号类别，本例为2PSK, 4PSK, GMSK, OQPSK, pi/4DQSK中的一个，还可以看Art网络的扩展性。(input signal instantaneous information on five characteristics : In the center is one of the instantaneous rate of the power spectral density of the maximum, is a center to the absolute value of the instantaneous rate of the standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component absolute standard deviation, Non-zero weak signal instantaneous phase of the nonlinear component standard deviation, In the center is one of the non-weak signal of the absolute value of the instantaneous frequency standard deviation, the identification of signal type, The cases of two PSK, 4PSK, GMSK, OQPSK, pi/4DQSK of one, Art can be viewed network scalability.)

说明：  Transformation in matlab alfa beta

Gabor小波变换技术对医学CT图像进行纹理特征分类时，由于图像拍摄角度的变化会造成分类的误差。针对以上问题，在Gabor小波变换的基础上提出一种用于分析旋转不变医学图像的方法。该方法采用旋转规范化，即特征元素的循环移位使规范化后所有的图像都具有相同的主方向。实验结果表明，加入旋转规范化循环算子的Gabor小波变换在医学CT图像纹理特征分类时能够达到较好的精确度。(Gabor wavelet transform lacks in its ability to classify the medical CT image if it’s rotation invariant image. Aiming at the problem, an approach is presented for rotation invariant medical texture classification based on Gabor wavelet transform. Rotation normalization is achieved by circular shift of the feature elements, so that all images have the same dominant direction. Experimental result shows that Gabor wavelet transform with circular operator of rotation normalization has well precision to classify the medical CT image.)