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vision
- 本书的目的主要是向读者展示傅里叶分析和小波的许多基础知识以及在信号分析方面的应用。全书分为8章和2个附录,前言部分是学习第1章至第7章的准备知识,即内积空间;第1章讲解傅里叶系列的基础知识;第2章讲解傅里叶变换;第3章介绍离散傅里叶变换以及快速傅里叶变换;第4章至第7章讨论小波,重点在于正交小波的构建;附录部分则介绍稍微复杂的一些技术主题以及演示概念或产生图形的MATLAB代码。许多关于小波的文章和参考书籍均要求读者具有复杂的数学背景知识,本书则只要求学生具有较好的微积分以及线性代数知识,通俗易
f10_1
- 小波变换在信号处理中的应用,包括压缩,去噪等,程序很简单-wavelet transform in signal processing applications, including compression, denoising, a very simple procedure
matlab1
- 我们知道,小波变换的一级分解过程是,原始信号分别进行低通、高通滤波,再分别进行二元下抽样,就得到低频、高频(也称为平均、细节)两部分系数;而多级分解则是对上一级分解得到的低频系数再进行小波分解,是一个递归过程。以下是一维小波分解的程序. -We know that a wavelet transform decomposition process is that the original signal were low-pass, high pass filter, and then
wavelet
- 小波包分析提取振动信号中的特征频率,以及能量谱分析计算-wavelet packet analysis vibration signal from the characteristic frequency, and the energy spectrum analysis -Extraction of wavelet packet analysis in the vibration signal characteristic frequency, as well as the calculati
wavelet
- 本程序可以实现利用小波变换对图像和数字信号的进行去噪-This procedure can be achieved using wavelet transform for image and digital signal Denoising
waveletexample
- 在matlab环境下,实现小波变换对信号处理方面的试验。-In the matlab environment, the realization of wavelet transform for signal processing experiments.
WaveletDSP
- 小波变换具有良好的时—频局部性,是分析奇异信号的重要方法定点DSP在工程中的厘用士分背通,具实现小波变换可以满足工程是实时性的要求文中简要介绍了小波变换理论及算法,并结合TI公司的16位定点说明算法的实现。 -Wavelet transform has a good time- frequency localization, is to analyze the singular signal an important means of fixed-point DSP in engineeri
dwtdenoising_ccslink
- 用离散小波变换实现语音去噪,并在TI 6711DSK上实现。可对实时语音信号进行去噪,开发环境CCStudio 3.1-Using discrete wavelet transform voice de-noising, and TI 6711DSK achieved. Of real-time voice signal denoising, CCStudio 3.1 development environment
Wavelet_De-noising_for_BSS
- 提出了三种小波滤波和盲源分离的结合方法,用于带噪信号的分离,-Three wavelet filtering and the combination of blind source separation method for separation of signals with noise,
waveltNN
- matlab格式源代码。功能:小波神经网络算法及其在信号处理中的应用。-matlab source code format. Function: wavelet neural network algorithm and its application in signal processing applications.
final
- 小波变换处理带噪语音信号,对于低信噪比的情况下相当有效,直接改文件名就可完成-Wavelet Transform of Noisy Speech signal processing for low SNR case quite effectively, direct to the file name can be completed
1125
- 基于小波转换对vc程序源代码!小波变换由于具有良好时频局部化特性,它通 过对不同的频率成分采用逐渐精细的采样步长,可 以聚焦到信号的任意细节,能很好地处理微弱或突 变信号-err
wavelet_max
- 小波模极大值原理在图像边缘提取和信号奇异点检测中的应用-Wavelet Modulus Maxima Principle in Image Edge Detection and Signal Singularity Detection
toolbox_wavelets
- 小波变换目前在各行各业都有应用,该小波变换工具箱,是一个外国研究所的研究成果,里面有其开发的各种小波工具,包括双正交波,多小波,等。在图像处理、信号处理等方面应用广泛-Wavelet transform applications in all walks of life, the wavelet transform toolbox, is a foreign institute of research results, which has its development of a variety
waveletanalysisandapplication
- 小波分析及其应用,详细介绍了小波变换原理和基本方法,还重点介绍小波变换在语音和图像处理、信号检测、多尺度边缘提取等领域的应用。-Wavelet analysis and applications, described in detail wavelet transform principles and basic methods, but also focuses on Wavelet Transform in the voice and image processing, signal det
featureextraction
- 利用MATLAB实现一维信号时间序列的,特征提取,其中包括ICA和基于小波包的方法。-Use MATLAB to achieve one-dimensional time series signal, feature extraction, including the ICA and the method based on wavelet packet.
selected_Algorithm_Collections_for_DSP_Application
- 基于matlab的新型信号处理算法集。包括模拟退火、遗传算法、反向传播神经网络、小波变换等等,对于统计信号处理很有参考价值。-Matlab based on a new type of signal processing algorithms. Including simulated annealing, genetic algorithm, back-propagation neural network, wavelet transform, etc., for statistical sig
JPEG2000_9_7_002.pdf
- 基于实数的二进制表示法,把CDF(Cohen,Daubechies and Feauveau)9/7双正交小波基的提升系数化为二进制,采用简单的移位一加操作代替结构复杂的浮点乘法器,从而实现了JPEG2000中9/7离散小波变换的定点计算.相对于浮点计算法,移位一加操作最大的优点是计算简单,特别易于超大规模集成电路实现,因而使硬件实时处理图像信号成为可能.实验仿真结果表明:在低压缩比的情况下,用移位一加操作重构的图像,其峰值信噪比(PSNR)只比浮点法低0.10 dB,当压缩比增大时,其PSNR
xiaobobianhua
- 利用小波变换检测突变点实验的实例,程序最后生成3个图像演示了该算法,分别为原数字信号、高斯函数作为基函数、高斯函数的一阶导数作为基函数的小波变换。-Mutation detection using wavelet transform examples of experimental points, the program generates the final three images to demonstrate the algorithm, namely, the original digi
fuzzy
- 一份介绍小波变换的论文,包括突变点的检测以及信号降噪等。-Introduce a wavelet transform of papers, including the detection of point mutations, as well as signals such as noise reduction.