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小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)

53小波变化的vc程序，很详细，有一维和二维，可以对图像进行处理。(53 wavelet transform vc program, very detailed, one-dimensional and two-dimensional image processing.)

db53小波的verilog硬件实现源码(Wavelet db53 Verilog hardware source)

数字基带传输基带信号，指未经调制的信号。这些信号的特征是其频谱从零频或很低频率开始，占据较宽的频带。 基带信号在传输前，必须经过一些处理或者某些变换（如码型变换、波形和频谱变换）才能送入信道中传输。处理或变换的目的是使信号的特性与信道的传输特性相匹配。 数字基带信号是消息代码的波形表示。表示形式有多种，有单极性、双极性波形，归零和非归零波形，差分波形、多电平波形之分，各自有不同的特点。 研究数字基带信号通过加性高斯白噪声信道的传输，并且假设信道除了叠加高斯噪声外，不会对信号产生其他失真。(matlabSimulation(pulse amplitude modulation) modulation signal in AWGN (additive white Gaussian noise AWGN (Additive White Gaussian Noise)) under the channel bit error rate and bit error rate performance, and compared with the theoretical value.)

关于小波变换的一些常用函数，有关多尺度变换，希望可以帮助您(Wavelet commonly used functions, on multi-scale transformation, I hope to help you)

图像加入水印提取水印的Matlab代码，包括的内容较多，能够完成各种实验的要求。(Extracted watermark image watermark to join the Matlab code, including the contents of more to complete the requirements of various experiments.)

说明：  LeGall(5，3)小波滤波器，其计算复杂度小、存储开销低、压缩效率高，已被JPEG2000标准采用。提升小波实例c语言实现(Lifting Wavelet Example C Language Implementation)

原子分解软件，包含各类字典（DCT，wavelet）(a software of atom decompose,including kinds of dictionaries(DCT,wavelet))

2.1 傅里叶变换 2.1.1 经典傅里叶变换 2.1.2 傅里叶变换的基本性质 2.1.3 快速傅里叶变换 2.1.4 短时傅里叶变换 2.2 小波分析与多分辨率分析的历史 2.3 小波分析与傅里叶变换的对比 2.4 小波变换 2.4.1 连续小波变换 2.4.2 离散小波变换 2.4.3 高维小波连续变换 2.5 常用小波基函数 2.5.1 小波函数 2.5.2 小波函数系 2.5.3 复数小波 2.6 构造紧支撑正常小波基 2.7 多分辨率分析与小波构造 2.8 分析小波包 2.8.1 小波包的定义及性质 2.8.2 分解小波包的空间 2.8.3 小波包算法(2.1 Fourier transform 2.1.1 classical Fourier transform 2.1.2 The basic properties of the Fourier transform 2.1.3 Fast Fourier Transform 2.1.4 short time Fourier transform 2.2 wavelet analysis and multi-resolution analysis of the history of 2.3 Wavelet Analysis and comparison of the Fourier transform 2.4 Wavelet Transform 2.4.1 Continuous Wavelet Transform 2.4.2 Discrete Wavelet Transform 2.4.3 Continuous high-dimensional wavelet transform 2.5 Common wavelet basis function 2.5.1 wavelet function 2.5.2 Department of wavelet function 2.5.3 Complex Wavelet 2.6 Construction of compactly supported wavelets normal More than 2.7 resolution analysis and wavelet construction 2.8 Analysis of Wavelet Packet 2.8.1 Definition and properties of wavelet packet 2.8.2 wavelet packet decomposition space 2.8.3 Wavelet Packet Algorithm)

利用小波变换实现和直方图均衡化相对比的图像的增强与分割.应该比较有用.分割也采取了几种技术的对比(using wavelet transform and histogram equalization relative ratio of image enhancement and segmentation. Be more useful. Pm cutting has taken several technical contrast)