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Fast Wavelet Transform
The fast wavelet transform is a mathematics, mathematical algorithm designed to turn a waveform or signal in the time domain into a sequence of coefficients based on an orthogonal basis of small finite waves, or wavelets. The transform can be easily extended to multidimensional signals, such as images, where the time domain is replaced with the space domain. This algorithm was introduced in 1989 by Stéphane Mallat. It has as theoretical foundation the device of a finitely generated, orthogonal multiresolution analysis (MRA). In the terms given there, one selects a sampling scale ''J'' with sampling rate of 2''J'' per unit interval, and projects the given signal ''f'' onto the space V_J; in theory by computing the dot product, scalar products :s^_n:=2^J \langle f(t),\varphi(2^J t-n) \rangle, where \varphi is the Wavelet#Scaling_function, scaling function of the chosen wavelet transform; in practice by any suitable sampling procedure under the condition that the signal is highly ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Mathematics
Mathematics is a field of study that discovers and organizes methods, Mathematical theory, theories and theorems that are developed and Mathematical proof, proved for the needs of empirical sciences and mathematics itself. There are many areas of mathematics, which include number theory (the study of numbers), algebra (the study of formulas and related structures), geometry (the study of shapes and spaces that contain them), Mathematical analysis, analysis (the study of continuous changes), and set theory (presently used as a foundation for all mathematics). Mathematics involves the description and manipulation of mathematical object, abstract objects that consist of either abstraction (mathematics), abstractions from nature orin modern mathematicspurely abstract entities that are stipulated to have certain properties, called axioms. Mathematics uses pure reason to proof (mathematics), prove properties of objects, a ''proof'' consisting of a succession of applications of in ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Wavelets - DWT
A wavelet is a wave-like oscillation with an amplitude that begins at zero, increases or decreases, and then returns to zero one or more times. Wavelets are termed a "brief oscillation". A taxonomy of wavelets has been established, based on the number and direction of its pulses. Wavelets are imbued with specific properties that make them useful for signal processing. For example, a wavelet could be created to have a frequency of middle C and a short duration of roughly one tenth of a second. If this wavelet were to be convolved with a signal created from the recording of a melody, then the resulting signal would be useful for determining when the middle C note appeared in the song. Mathematically, a wavelet correlates with a signal if a portion of the signal is similar. Correlation is at the core of many practical wavelet applications. As a mathematical tool, wavelets can be used to extract information from many kinds of data, including audio signals and images. Sets of ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ronald Coifman
Ronald Raphael Coifman (; born June 29, 1941) is a Sterling professor of Mathematics at Yale University. Coifman earned a doctorate from the University of Geneva in 1965, supervised by Jovan Karamata. Coifman is a member of the American Academy of Arts and Sciences, the Connecticut Academy of Science and Engineering, and the National Academy of Sciences. He is a recipient of the 1996 DARPA Sustained Excellence Award, the 1996 Connecticut Science Medal, the 1999 Pioneer Award of the International Society for Industrial and Applied Science, and the 1999 National Medal of Science. Prior to teaching at Yale, Coifman taught at Washington University in St. Louis and the University of Chicago. In 2013, he co-founded ThetaRay, a cyber security and big data analytics company. In 2018, he received the Rolf Schock Prize for Mathematics. In 2024 he was awarded the George David Birkhoff Prize. References External links Scientific Data Has Become So Complex, We Have to Invent New Mat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gregory Beylkin
Gregory Beylkin (born 16 March 1953) is a Russian–American mathematician. Education and career He studied from 1970 to 1975 at the University of Leningrad, with Diploma in Mathematics in November 1975. From 1976 to 1979 he was a research scientist at the Research Institute of Ore Geophysics, Leningrad. From 1980 to 1982 he was a graduate student at New York University, where he received his PhD under the supervision of Peter Lax. From 1982 to 1983 Beylkin was an associate research scientist at the Courant Institute of Mathematical Sciences. From 1983 to 1991 he was a member of the professional staff of Schlumberger-Doll Research in Ridgefield, Connecticut. Since 1991 he has been a professor in the Department of Applied Mathematics at the University of Colorado Boulder. He was a visiting professor at Yale University, the University of Minnesota, and the Mittag-Leffler Institute and participated in 2012 and 2015 in the summer seminar on "Applied Harmonic Analysis and Sparse Appro ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Barbara Burke Hubbard
Barbara Burke Hubbard (born 1948) is an American science journalist, mathematics popularizer, textbook author, and book publisher, known for her books on wavelet transforms and multivariable calculus. Life Burke Hubbard is the daughter of ''Los Angeles Times'' reporter Vincent J. Burke, and spent a year in high school living in Moscow when Burke was stationed there in 1964. She was an undergraduate at Harvard University, initially majoring in biology but switching to English, and graduating in 1969. She became a science writer for the Massachusetts Institute of Technology and a journalist for '' The Ithaca Journal'', and was the 1981 winner of the AAAS Westinghouse Science Journalism Award in the small newspaper category, for her articles on acid rain in ''The Ithaca Journal''. She married mathematician John H. Hubbard, with whom she has four children, and with her family has split her time between Ithaca, New York, and Marseille, France, with shorter-term stays elsewhere. Bo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cristina Pereyra
María Cristina Pereyra (born 1964) is a Venezuelan mathematician. She is a professor of mathematics and statistics at the University of New Mexico, and the author of several books on wavelets and harmonic analysis. Pereyra was an American Mathematical Society (AMS) Council member at large from 2019 - 2021. Education and employment Pereyra was a member of the Venezuelan team for the 1981 and 1982 International Mathematical Olympiads. She earned a licenciado (the equivalent of a bachelor's degree) in mathematics in 1986 from the Central University of Venezuela. She went to Yale University for graduate studies, completing her Ph.D. there in 1993. Her dissertation, ''Sobolev Spaces On Lipschitz Curves: Paraproducts, Inverses And Some Related Operators'', was supervised by Peter Jones. After working for three years as an instructor at Princeton University, she joined the University of New Mexico faculty in 1996. Books Pereyra is the author or editor of: *''Lecture Notes on Dyadic Ha ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fast Fourier Transform
A fast Fourier transform (FFT) is an algorithm that computes the discrete Fourier transform (DFT) of a sequence, or its inverse (IDFT). A Fourier transform converts a signal from its original domain (often time or space) to a representation in the frequency domain and vice versa. The DFT is obtained by decomposing a sequence of values into components of different frequencies. This operation is useful in many fields, but computing it directly from the definition is often too slow to be practical. An FFT rapidly computes such transformations by Matrix decomposition, factorizing the DFT matrix into a product of Sparse matrix, sparse (mostly zero) factors. As a result, it manages to reduce the Computational complexity theory, complexity of computing the DFT from O(n^2), which arises if one simply applies the definition of DFT, to O(n \log n), where is the data size. The difference in speed can be enormous, especially for long data sets where may be in the thousands or millions. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lifting Scheme
The lifting scheme is a technique for both designing wavelets and performing the discrete wavelet transform (DWT). In an implementation, it is often worthwhile to merge these steps and design the wavelet filters ''while'' performing the wavelet transform. This is then called the second-generation wavelet transform. The technique was introduced by Wim Sweldens. The lifting scheme factorizes any discrete wavelet transform with finite filters into a series of elementary convolution operators, so-called lifting steps, which reduces the number of arithmetic operations by nearly a factor two. Treatment of signal boundaries is also simplified. The discrete wavelet transform applies several filters separately to the same signal. In contrast to that, for the lifting scheme, the signal is divided like a zipper. Then a series of convolution–accumulate operations across the divided signals is applied. Basics The simplest version of a forward wavelet transform expressed in the lifting s ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Hilbert Space
In mathematics, a Hilbert space is a real number, real or complex number, complex inner product space that is also a complete metric space with respect to the metric induced by the inner product. It generalizes the notion of Euclidean space. The inner product allows lengths and angles to be defined. Furthermore, Complete metric space, completeness means that there are enough limit (mathematics), limits in the space to allow the techniques of calculus to be used. A Hilbert space is a special case of a Banach space. Hilbert spaces were studied beginning in the first decade of the 20th century by David Hilbert, Erhard Schmidt, and Frigyes Riesz. They are indispensable tools in the theories of partial differential equations, mathematical formulation of quantum mechanics, quantum mechanics, Fourier analysis (which includes applications to signal processing and heat transfer), and ergodic theory (which forms the mathematical underpinning of thermodynamics). John von Neumann coined the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Upsampling
In digital signal processing, upsampling, expansion, and interpolation are terms associated with the process of sample rate conversion, resampling in a multi-rate digital signal processing system. ''Upsampling'' can be synonymous with ''expansion'', or it can describe an entire process of ''expansion'' and filtering (''interpolation''). When upsampling is performed on a sequence of samples of a ''signal'' or other continuous function, it produces an approximation of the sequence that would have been obtained by sampling the signal at a higher rate (or Dots per inch, density, as in the case of a photograph). For example, if compact disc audio at 44,100 samples/second is upsampled by a factor of 5/4, the resulting sample-rate is 55,125. Upsampling by an integer factor Rate increase by an integer factor L can be explained as a 2-step process, with an equivalent implementation that is more efficient: #Expansion: Create a sequence, x_L[n], comprising the original samples, x[n], separat ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Linear Subspace
In mathematics, the term ''linear'' is used in two distinct senses for two different properties: * linearity of a ''function (mathematics), function'' (or ''mapping (mathematics), mapping''); * linearity of a ''polynomial''. An example of a linear function is the function defined by f(x)=(ax,bx) that maps the real line to a line in the Euclidean plane R2 that passes through the origin. An example of a linear polynomial in the variables X, Y and Z is aX+bY+cZ+d. Linearity of a mapping is closely related to ''Proportionality (mathematics), proportionality''. Examples in physics include the linear relationship of voltage and Electric current, current in an electrical conductor (Ohm's law), and the relationship of mass and weight. By contrast, more complicated relationships, such as between velocity and kinetic energy, are ''Nonlinear system, nonlinear''. Generalized for functions in more than one dimension (mathematics), dimension, linearity means the property of a function of b ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adjoint Filter
In signal processing, the adjoint filter mask h^* of a filter mask h is reversed in time and the elements are complex conjugated. :(h^*)_k = \overline Its name is derived from the fact that the convolution with the adjoint filter is the adjoint operator of the original filter, with respect to the Hilbert space \ell_2 of the sequences in which the inner product is the Euclidean norm. :\langle h*x, y \rangle = \langle x, h^* * y \rangle The autocorrelation Autocorrelation, sometimes known as serial correlation in the discrete time case, measures the correlation of a signal with a delayed copy of itself. Essentially, it quantifies the similarity between observations of a random variable at differe ... of a signal x can be written as x^* * x. Properties * ^* = h * (h*g)^* = h^* * g^* * (h\leftarrow k)^* = h^* \rightarrow k References Digital signal processing {{signal-processing-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
