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Multidelay Block Frequency Domain Adaptive Filter
The multidelay block frequency domain adaptive filter (MDF) algorithm is a block-based frequency domain implementation of the (normalised) Least mean squares filter (LMS) algorithm. Introduction The MDF algorithm is based on the fact that convolutions may be efficiently computed in the frequency domain (thanks to the fast Fourier transform). However, the algorithm differs from the fast LMS algorithm in that block size it uses may be smaller than the filter length. If both are equal, then MDF reduces to the FLMS algorithm. The advantages of MDF over the (N)LMS algorithm are: * Lower algorithmic complexity * Partial de-correlation of the input (which 'may' lead to faster convergence) Variable definitions Let N be the length of the processing blocks, K be the number of blocks and \mathbf denote the 2Nx2N Fourier transform matrix. The variables are defined as: : \underline(\ell) = \mathbf\left \mathbf_, e(\ell N),\dots,e(\ell N-N-1) \rightT : \underline_k(\ell) = \mathrm \left\ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Least Mean Squares Filter
Least mean squares (LMS) algorithms are a class of adaptive filter used to mimic a desired filter by finding the filter coefficients that relate to producing the least mean square of the error signal (difference between the desired and the actual signal). It is a stochastic gradient descent method in that the filter is only adapted based on the error at the current time. It was invented in 1960 by Stanford University professor Bernard Widrow and his first Ph.D. student, Ted Hoff. Problem formulation Relationship to the Wiener filter The realization of the causal Wiener filter looks a lot like the solution to the least squares estimate, except in the signal processing domain. The least squares solution, for input matrix \mathbf and output vector \boldsymbol y is : \boldsymbol = (\mathbf ^\mathbf\mathbf)^\mathbf^\boldsymbol y . The FIR least mean squares filter is related to the Wiener filter, but minimizing the error criterion of the former does not rely on cross-corr ... [...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). Fourier analysis 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 factorizing the DFT matrix into a product of sparse (mostly zero) factors. As a result, it manages to reduce the complexity of computing the DFT from O\left(N^2\right), which arises if one simply applies the definition of DFT, to O(N \log N), where N is the data size. The difference in speed can be enormous, especially for long data sets where ''N'' may be in the thousands or millions. In the presence of round-off error, many FFT algorithm ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Fast LMS Algorithm
Fast or FAST may refer to: * Fast (noun), high speed or velocity * Fast (noun, verb), to practice fasting, abstaining from food and/or water for a certain period of time Acronyms and coded Computing and software * ''Faceted Application of Subject Terminology'', a thesaurus of subject headings * Facilitated Application Specification Techniques, a team-oriented approach for requirement gathering * FAST protocol, an adaptation of the FIX protocol, optimized for streaming * FAST TCP, a TCP congestion avoidance algorithm * FAST and later as Fast Search & Transfer, a Norwegian company focusing on data search technologies * Fatigue Avoidance Scheduling Tool, software to develop work schedules * Features from accelerated segment test, computer vision method for corner detection * Federation Against Software Theft, a UK organization that pursues those who illegally distribute software * Feedback arc set in Tournaments, a computational problem in graph theory * USENIX Conference on File a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lms Filter
LMS may refer to: Science and technology * Labeled magnitude scale, a scaling technique * Learning management system, education software * Least mean squares filter, producing least mean square error * Leiomyosarcoma, a rare form of cancer * Lenz microphthalmia syndrome * Computerised Library management system * Licentiate in Medicine and Surgery, a degree in India * LMS color space * Laboratory information management system (but usually LIMS) Organisations * Latin Mass Society of England and Wales * List of Marjan Šarec, a Slovenian political party * London Mathematical Society * London, Midland and Scottish Railway * London Missionary Society * ''League of Legends'' Master Series * Loving Municipal Schools Entertainment * Last man standing (gaming), a type of video game * LMS, family band of Denroy Morgan Other uses * Leamington Spa railway station code, England * Local Mitigation Strategy * Local Management of Schools, in the Education Reform Act 1988 The Education Refor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
International Conference On Acoustics, Speech, And Signal Processing
ICASSP, the International Conference on Acoustics, Speech, and Signal Processing, is an annual flagship conference organized of IEEE Signal Processing Society. All papers included in its proceedings have been indexed by Ei Compendex. The first ICASSP was held in 1976 in Philadelphia, Pennsylvania based on the success of a conference in Massachusetts four years earlier that had focused specifically on speech signals. As ranked by Google Scholar's h-index The ''h''-index is an author-level metric that measures both the productivity and citation impact of the publications, initially used for an individual scientist or scholar. The ''h''-index correlates with obvious success indicators such as winn ... metric in 2016, ICASSP has the highest h-index of any conference in Signal Processing field. Also, It is considered a high level conference in signal processing and, for example, obtained an 'A1' rating from the Brazilian ministry of education based on its H-index. References ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Adaptive Filter
An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimization algorithm. Because of the complexity of the optimization algorithms, almost all adaptive filters are digital filters. Adaptive filters are required for some applications because some parameters of the desired processing operation (for instance, the locations of reflective surfaces in a reverberant space) are not known in advance or are changing. The closed loop adaptive filter uses feedback in the form of an error signal to refine its transfer function. Generally speaking, the closed loop adaptive process involves the use of a cost function, which is a criterion for optimum performance of the filter, to feed an algorithm, which determines how to modify filter transfer function to minimize the cost on the next iteration. The most common cost function is the mean square of the error signal. As the pow ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Recursive Least Squares
Recursive least squares (RLS) is an adaptive filter algorithm that recursively finds the coefficients that minimize a weighted linear least squares cost function relating to the input signals. This approach is in contrast to other algorithms such as the least mean squares (LMS) that aim to reduce the mean square error. In the derivation of the RLS, the input signals are considered deterministic, while for the LMS and similar algorithms they are considered stochastic. Compared to most of its competitors, the RLS exhibits extremely fast convergence. However, this benefit comes at the cost of high computational complexity. Motivation RLS was discovered by Gauss but lay unused or ignored until 1950 when Plackett rediscovered the original work of Gauss from 1821. In general, the RLS can be used to solve any problem that can be solved by adaptive filters. For example, suppose that a signal d(n) is transmitted over an echoey, noisy channel that causes it to be received as :x(n)=\sum_^q ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Least Squares
The method of least squares is a standard approach in regression analysis to approximate the solution of overdetermined systems (sets of equations in which there are more equations than unknowns) by minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each individual equation. The most important application is in data fitting. When the problem has substantial uncertainties in the independent variable (the ''x'' variable), then simple regression and least-squares methods have problems; in such cases, the methodology required for fitting errors-in-variables models may be considered instead of that for least squares. Least squares problems fall into two categories: linear or ordinary least squares and nonlinear least squares, depending on whether or not the residuals are linear in all unknowns. The linear least-squares problem occurs in statistical regressio ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Digital Signal Processing
Digital signal processing (DSP) is the use of digital processing, such as by computers or more specialized digital signal processors, to perform a wide variety of signal processing operations. The digital signals processed in this manner are a sequence of numbers that represent samples of a continuous variable in a domain such as time, space, or frequency. In digital electronics, a digital signal is represented as a pulse train, which is typically generated by the switching of a transistor. Digital signal processing and analog signal processing are subfields of signal processing. DSP applications include audio and speech processing, sonar, radar and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, data compression, video coding, audio coding, image compression, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. DSP can involve linear or nonli ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
