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Ch1799
- 小波工具箱的应用基础 395 16.1 一维小波分析的应用 395 16.1.1 小波分解在普通信号分析中的应用 395 16.1.2 小波变换在信号特征检测中的应用 411 16.2 二维小波分析的应用 417 16.2.1 小波分析在图像平滑中的应用 417 16.2.2 小波分析在图像增强中的应用 418 16.2.3 小波分析在图像融合中的应用 420 16.3 小波包分析的应用 422 16.3.1 小波包在信号时频分析中的应用 423 16.
watermarkt1
- 基于小波零树特性的视觉感知度模型的优化方案, 给出了两种水印算法: 一种算法嵌入的是高斯序列水印, 通过相关检测实现盲检测 另一种算法嵌入的是二值图像水印, 水印的提取是非盲提取。这两种算法在所有重要小波系数( 包括最低频系数) 中嵌入水印, 以达到最大化水印嵌入量的目的, 并结合感知度模型在水印的透明性和鲁棒性之间实现了较好的平衡, 对于常见的图像处理操作, 特别是对于JPEG 和小波压缩均有较好的鲁棒性。-based on wavelet zerotree visual perception
watermark_2
- 提出了一种离散小波变换域实现图像水印的方法。这种算法充分利用小波变换的特点,把原始图像及水印图像塔式分解,在多分辨率分解后的相同的频段来嵌入水印信息。该方法也利用了人眼视觉特性,算法简单而有效。实验证明,该算法较好地解决了水印不可见性与鲁棒性之间的矛盾,对常见的水印攻击都有较强的鲁棒性。-presents a discrete wavelet transform domain image watermarking method. This algorithm using wavelet tran
someproblem
- 几篇有关解决小波分析过程中频率混淆问题的论文，供大家阅读参考-Several wavelet analysis for resolving the issue of confusion of the process of the frequency of the papers, for all to read the reference
Wavelet1D
- 本例程主要演示了一维小波变换，小波算法是一种基于时域到频域的变换，可以得到信号频率和时间的关系。-The main demonstration of the routine of one-dimensional wavelet transform, wavelet-based algorithm is a time-domain to frequency domain transform, the signal can be frequency and time.
Three-non-stationary-time-frequency-signal
- 三种非平稳信号时频分析的方法 窗口傅里叶变换、wigner分布和小波变换-Three non-stationary time-frequency analysis window Fourier transform, wigner distribution and wavelet transform
xiaoxingshuzixitong
- 本课题研究的主要内容是在空间域直接处理图像的基础上，几种典型的变 换域快速算法分析与研究及这些快速算法的程序设计实现。还研究了图像增强 中的变换域处理方法，主要针对几种典型变换域滤波器及其程序实现；最后对 小波变换的算法分析及在图像压缩中的应用进行了理论研究。-This task includes a series of speedy arithmetic analysis and their programme implement in frequency domain aft
vm
- Owing to the broad application value of audio watermarking in remote transmission and mobile extraction, it is very important to study watermarking approaches against A/D and D/A conversion. Based on wavelet decomposition and cepstrum technol
amorph
- Owing to the broad application value of audio watermarking in remote transmission and mobile extraction, it is very important to study watermarking approaches against A/D and D/A conversion. Based on wavelet decomposition and cepstrum technol
vm2
- Owing to the broad application value of audio watermarking in remote transmission and mobile extraction, it is very important to study watermarking approaches against A/D and D/A conversion. Based on wavelet decomposition and cepstrum technol
wavelets
- an introduction to wavelets -Wavelets are mathematical functions that cut up data into di® erent frequency components, and then study each component with a resolution matched to its scale. They have advantages over traditional Fourier method
amethodforimagefusion
- 文中的方法是把图像分块，小波分解得到低频分量、高频分量，然后计算每一块的对比度，把图像块划分为清晰块、模糊块，把清晰块和模糊块相邻的区域定义为边界区域，融合时，直接选取清晰块作为融合后的相应块，对于边界区域，在小波分解的基础上采用基于对比度的像素选取的方法进行处理。-Paper, the method is to image segmentation, wavelet decomposition are low frequency, high frequency components, then
1003.5627
- Wavelet-Based Mel-Frequency CepstralCoefficients for Speaker Identification using Hidden Markov Models
time_frequency
- 这是一篇现代通信原理课程的作业报告.题目为几种时频分析方法比较及应用.详细介绍了短时傅里叶变换、小波变换、魏格纳—威利分布和Cohen类时频分布这4种典型时频分析方法,并作了比较-This is a modern communication Principle operating report. Entitled Comparison of several time-frequency analysis and 应用. 详细 Jieshao the short time Fourier tran
A-crop-phenology-detection-method-using-time-seri
- Information of crop phenology is essential for evaluating crop productivity and crop management. Therefore we developed a new method for remotely determining phenological stages of paddy rice. The method consists of three procedures: (i) prescr ipt
ECG-Detection-use-wavelet
- 本文把小波变换应用于心电信号的识别。探讨了伸缩尺度和伪频率(译自pseudo—frequency)-~．间的关系；利用二进双正 交样条小波对室扑信号按Mallat算法进行小波分解；提出了心室扑动和心室颤动信号的小波变换识别方法-Wavelet transform in used to identify the ECG si a1．The relation between scale and pseudo—frequency is discussed．The ventrlcular flu
niantanxing
- 粘弹性地震波的衰减不仅与传播时间有关，而且与子波的频率、速度场的分布、射线路经、地下构造展布都有关，因此，仅仅利用反Q滤波对粘弹性的吸收和频散做一维补偿不能完全的恢复地震波长的本来特征。-Viscoelastic seismic wave attenuation is not only associated with the propagation time, and and wavelet frequency distribution of the velocity field, the ra
Noise-reduction-algorithm
- 对设备进行故障诊断的主要方法就是测量故障 设备的振动或噪声, 并对其进行分析, 从而找出故障原因。然而振动或噪声信号中除了对分析故障有用的信息外, 还有大量的噪声成分。只有有效地滤除噪声, 才能获得有用的信息, 从而得到可靠的分析结论。传统的滤噪方法是将被噪声污染的信号通过一个滤波器, 滤掉噪声频率成分。但对于短时瞬态信号、非平稳信号、含宽带噪声的信号, 采用传统处理方法有着明显的局限性。小波变换为信号去噪提供了一种有效的方法, 小波阈值去噪具有传统方法不可比拟的优越性。但是小波分解的频域重
wavelet-packets-analysis
- 针对风力发电机组传动系统故障时特征量提取困难的问题,提出了改进的小波包结合包络谱的故障诊断新方法。深入研究了小波包频带错乱的问题，对小波包实施了改进，消除了频带错乱的缺陷-In view of the wind turbine drive system characteristics, failure and difficult problems, puts forward the improved wavelet packet combining spectral envelope, a ne
wavelet
- With the development of power systems and the extensive application of nonlinear elements in the electricity system, the problem of ferroresonance do harm to the network and electricity facilities has become more prominent. Wavelet analysis h