Extractions: CERNLIB The CERN Program Library is a large collection of general purpose programs maintained and offered in both source and object code form on the CERN central computers. Most of these programs were developed at CERN and are therefore oriented towards the needs of a physics research laboratory. Nearly all, however, are of a general mathematical or data-handling nature, applicable to a wide range of problems. Current Version: License Type: Free of charge to all HEP users. http://hepwww.ph.qmw.ac.uk/HEPpc/linux-hep-faq.html#3-2 Home Site: http://wwwinfo.cern.ch/asd/cernlib/overview.html http://hepwww.ph.qmw.ac.uk/HEPpc/linux-hep-faq.html#3 (Linux specific information) Source Code Availability: Yes Available Binary Packages:
Amara's Wavelet Page Introduction to wavelets with links to many other resources by Amara Graps. http://www.amara.com/current/wavelet.html
Extractions: The fundamental idea behind wavelets is to analyze according to scale. Indeed, some researchers in the wavelet field feel that, by using wavelets, one is adopting a whole new mindset or perspective in processing data. Wavelets are functions that satisfy certain mathematical requirements and are used in representing data or other functions. This idea is not new. Approximation using superposition of functions has existed since the early 1800's, when Joseph Fourier discovered that he could superpose sines and cosines to represent other functions. However, in wavelet analysis, the scale that one uses in looking at data plays a special role. Wavelet algorithms process data at different scales or resolutions. If we look at a signal with alarge "window," we would notice gross features. Similarly, if we look at a signal with a small "window," we would notice small discontinuities. The result in wavelet analysis is to "see the forest and the trees." Can you see why these features make wavelets interesting and useful? For many decades, scientists have wanted more appropriate functions than the the sines and cosines which comprise the bases of Fourier analysis, to approximate choppy signals. By their definition, these functions are non-local (and stretch out to infinity), and therefore do a very poor job in approximating sharp spikes. But with wavelet analysis, we can use approximating functions that are contained neatly in finite domains. Wavelets are well-suited for approximating data with sharp discontinuities.
Computer Graphics Bookmarks Links on computer vision research including wavelet-related sites. http://graphics.lcs.mit.edu/~fredo/Book/vision.html
Extractions: If you have comments, links to add, links to update, drop me an e-mail CVonline The Evolving, Distributed, Non-Proprietary, On-Line Compendium of Computer Vision Ken Castleman's Digital Image Processing Page Computer Vision Handbook Computer Vision Home Page Paul Heckbert's Collection of Mesh Generation Links ... comp. geom.
Extractions: //new fadeshow(IMAGES_ARRAY_NAME, slideshow_width, slideshow_height, borderwidth, delay, pause (0=no, 1=yes), optionalRandomOrder) new fadeshow(homepage, 552, 287, 1, 2500, 1) Oasys Mobile is excited to release six brand new iPhone games, iShot Machine Merlin's Legacy , and Crazy Eights . Also check out College Fan Zone and Tricky Tracks the new release for Verizon and Alltel. Personalize your mobile phone with College and Greek wallpapers and ringtones. View All New Releases The iPhone app that offers you hours of fun at bars, parties, or even your kitchen. Over 3000 shot recipes to choose from!
Extractions: var host_pre = "http://www"; Home Select Country Contact Us Store Search Create Account Log In Solutions Academia ... Documentation Other Resources Technical Literature User Stories Related Books technical computing environment with graphical tools and command-line functions for developing wavelet-based algorithms for the analysis, synthesis, denoising, and compression of signals and images. Wavelet analysis provides more precise information about signal data than other signal analysis techniques, such as Fourier.
Extractions: Mathematica for Students ... Give us feedback Sign up for our newsletter: Discover the power of wavelets! Wavelet analysis, in contrast to Fourier analysis, uses approximating functions that are localized in both time and frequency space. It is this unique characteristic that makes wavelets particularly useful, for example, in approximating data with sharp discontinuities. Engineers, physicists, astronomers, geologists, medical researchers, and others explore the extraordinary array of potential applications of wavelet analysis. Ranging from signal and image processing to data analysis, Wavelet Explorer brings this broad spectrum of wavelet analysis tools to your desktop. Wavelet Explorer 's ready-to-use functions and utilities let you apply a variety of wavelet transforms to your projects. Generate commonly used filters such as the Daubechies' extremal phase and least asymmetric filters, coiflets, spline filters, and more. Visualize wavelets and wavelet packets and zoom in on their details. You can transform your data to a host of wavelet bases, wavelet packet bases, or local trigonometric bases and do inverse transforms in one and two dimensions. Then view the transform in time-frequency space, selecting different bases and boundary conditions. Data compression and denoising are surprisingly simple procedures with Wavelet Explorer 's built-in functions.
Extractions: Home WavBox FirWav Papers ... Contact The WavBox Software logo image, shown above, is displayed as a "splash screen" image on start-up of the software. This composite image logo has been designed to reveal some of the fundamental aspects of wavelet transforms. It shows the most famous Daubechies wavelets (those corresponding to filters with four coefficients) and the characteristic tiling of the time-frequency plane with tall thin tiles at high frequencies and short fat tiles at low frequencies. WavBox Software (Toolsmiths Wavelet Toolbox) is the original MATLAB Wavelet Toolbox, the first available as free software in 1991, and
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