搜索资源列表
DiscreteFourier
- 采用Visual c++ 进行图像处理,已经经过检测,非常实用,本源码主要是离散傅立叶分析-for image processing, have been tested, the very practical, The main source of discrete Fourier analysis
sft_wt.rar
- 给定函数,变换到频域内,比较短时傅里叶变换大、小视窗和小波变换的区别,生成时频分析图,A given function, transform the frequency domain, more short-time Fourier transform, and a small window and the difference between wavelet transform to generate time-frequency analysis
signal-fourier-analysis
- 信号傅里叶变换的matlab程序,包括对幅频和相频的图形绘制-Signal Fourier transform matlab program, including the magnitude and phase frequency of the graphics rendering
Analysis
- 分析FFT,LPC等变换,对信号处理的经典算法进行分析-Descr iption and detailed explanation on Fourier Transform, some FFT, LPC etc. Runable project demonstrates DCT transform on continuous audio, show and edit audio source with different zooming and view.
Frequencydomainimageprocessing
- 傅立叶变换是线性系统分析的一个有力工具,是信号处理中最重要、应用最广泛的变换,利用频域中特有的性质,可以使图像处理过程更加简单、有效,对于迂回解决图像处理中的难题非常有帮助,被广泛应用于数字图像处理中,-Fourier transform is a linear system analysis a powerful tool for signal processing are the most important and most widely used transform, the use o
wavelet_report
- 信号处理是结构健康监测系统一个重要组成部分。小波变换作为有效的信号处理工具能对被分析信号进行更细致分析,获得比傅立叶分析更多的信号特征。将小波分析应用于航空结构材料的结构健康监测中,对检测信号进行时频局部化处理,获得与结构状态相联系的特征。-Signal processing is a structural health monitoring system an important part. Wavelet transform as an effective signal processing
xiaobobianhuantux
- 小波变换是一种快速发展和比较流行的信号分析方法, 其在图像处理中有非常重要的应用, 包括图像压缩, 图像去噪, 图像融合, 图像分解, 图像增强等。小波分析是傅立叶分析思想方法的发展与延拓。除了连续小波 (CWT)、离散小波(DWT), 还有小波包avelet Packet)和多维小波。本文主要介绍小波变换的发展及其在图像处理、的应用-Wavelet transform is a fast-growing and more popular method of signal analysis,
2008172870
- 本文详细介绍了指纹识别技术的预处理算法,其中包括MATLAB算法仿真部分和DSP实现部分,并着重研究了预处理算法中的指纹图像归一化、图象滤波增强、图像分割、二值化、细化等关键技术。本文提出了改进的Gabor滤波算法,同时对其他预处理部分算法进行了优化,并将傅立叶分析方法应用于指纹图象处理研究中,采用MATLAB实现了本文讨论的所有算法。-This paper describes a fingerprint recognition algorithm technologies, including
ImageProcess
- VC++6编译环境,实现平滑,锐化,边缘增强,边缘提取(3种算法),边缘检测,中值滤波,频域变换(傅里叶分析FFT,离散余弦变换DCT)-VC++6 compiler environment, to achieve smooth, sharpen, edge enhancement, edge detection (three kinds of algorithm), edge detection, median filtering, frequency domain transform (Fo
MATLAB_Medical_Image_Process_Experiments
- MATLAB医学影像处理实验(内含14个原代码及教学的说明) (1)Plot a sine function using MATLAB, and write the data into a file (2)Read data from a file, plot a SINC function, and append the result back to the same file (3)Plot a Gaussian distribution using MATLAB (4)Fo
WFTgui
- Windowed Fourier transform for fringe pattern analysis (with GUI) -• Run WFT in MATLAB environment. All processed data are automatically saved in result.mat 4. File list o wft2fw.m: the basic WFT algorithm. o unwrapping_qg_trim.m: quali
matlab
- 小波分析是傅立叶分析思想方法的发展与延拓-Wavelet analysis is a Fourier analysis of the development and extension thinking
lFusion
- 小波变换是在傅立叶变换的基础上发展起来的,它优于傅立叶分析的地方是它在空域和时域都是局部化的,其局部化格式随频率自动变换,在高频处取窄的时(空)间窗,在低频处取宽的时(空)窗,适合处理非平稳信号,在图像处理、模式识别、机器人视觉、量子力学等领域得到广泛应用。-Wavelet transform is a Fourier transform developed on the basis, it is better than Fourier analysis of the place is that
Fourier-analysis-and-wavelet
- 通过对傅里叶分析和小波分析的详细比较, 展示小波分析的特点和优越性, 有助于深化对小波分析的认识和理解.-By Fourier analysis and wavelet analysis of a detailed comparison, showing the characteristics and advantages of wavelet analysis, wavelet analysis can help to deepen knowledge and understanding
Wavelet-and-Fourier-Analysis
- 小波与傅里叶分析基础中文版,附录中有相关MATLAB程序-Wavelet and Fourier analysis based on the Chinese version of MATLAB programs relevant appendix
Wavelet-Analysis
- 小波分析是建立在泛函分析、调和分析、数值分析、逼近论和傅里叶分析等的基础上发展起来的新的时频分析方法。与经典的傅里叶分析相比较,小波变换是空间(时间)和频率的局部变换,因而能有效地从信号中提取信息,因此小波分析有着许多显著的优点。小波变换是空间(时间)和频率的局部变换,因而能有效地从信号中提取信息。通过伸缩和平移等运算功能可对函数或信号进行多尺度的细化分析,解决了Fourier变换不能解决的许多困难问题。 小波分析是时间—尺度分析和多分辨分析的一种新技术,它在信号分析、语音合成、图像识别、计
Wavelet-algorithm
- 小波分析诞生于20世纪80年代, 被认为是调和分析即现代Fourier分析发展的一个崭新阶段。众多高新技术以数学为基础,而小波分析被誉为“数学显微镜”,这就决定了它在高科技研究领域重要的地位。目前, 它在模式识别、图像处理、语音处理、故障诊断、地球物理勘探、分形理论、空气动力学与流体力学上的应用都得到了广泛深入的研究,甚至在金融、证券、股票等社会科学方面都有小波分析的应用研究-Wavelet analysis was born in the 1980s, is considered the mo
Wavelet-Analysis
- 对于非平稳信号的分析不能依靠傅里叶变换,但可以采用时频分析的方法,其中加窗傅里叶变换是最简单的一种。但是,它有很大的局限性:当基本窗函数一旦取定,窗口的时窗宽度和频窗宽度就固定了,不会随时域和频域的位移而变化。-For non-stationary signal analysis can not rely on Fourier transform, but you can use time-frequency analysis method, in which the windowed Four
An-improved-Hilbert-Huang-method-for-analysis-of-
- The Hilbert–Huang method is presented with modifications, for time-frequency analysis of distorted power quality signals. The empirical mode decomposition (EMD) is enhanced with masking signals based on fast Fourier transform (FFT), for separat
Wavelets
- 1 Haar Wavelets 1.1 The Haar transform 1.2 Conservation and compaction of energy 1.3 Haar wavelets 1.4 Multiresolution analysis 1.5 Compression of audio signals 1.6 Removing noise from audio signals 1.7 Notes and references 2 Daub ech