نتایج جستجو برای: known algorithm that deals with signals is matching pursuit mp originally
تعداد نتایج: 11790243 فیلتر نتایج به سال:
Glitches are transients of environmental or instrumental origin appearing in the data channel of existing large baseline interferometer based gravitational wave detectors. Their presence limits severely the performance of gravitational wave detection/estimation algorithms based on the customary Gaussian noise assumption, and requires adopting ad-hoc data laundering techniques. Modeling glitches...
Matching pursuit (MP) is an adaptive signal decomposition technique and can be applied to process Lamb waves, such as denoising, wave parameter estimation, and feature extraction, for health monitoring applications. This paper explored matching pursuit decomposition using Gaussian and chirplet dictionaries to decompose/approximate Lamb waves and extract wave parameters. While Gaussian dictionar...
the space now known as complete erdos space ec was introduced by paul erdos in 1940 as the closed subspace of the hilbert space ?2 consisting of all vectors such that every coordinate is in the convergent sequence {0} ? { 1 n : n ? n}. in a solution to a problem posed by lex g. oversteegen we present simple and useful topological characterizations of ec. as an application we determine the ...
Analysis of nonstationary signals, such as music signals, is a challenging task. The purpose of this study is to explore an efficient and powerful technique to analyze and classify music signals in higher frequency range (44.1 kHz). The pursuit methods are good tools for this purpose, but they aimed at representing the signals rather than classifying them as in Y. Paragakin et al., 2009. Among ...
Polytope Faces Pursuit (PFP) is a greedy algorithm that approximates the sparse solutions recovered by 1 regularised least-squares (Lasso) [4,10] in a similar vein to (Orthogonal) Matching Pursuit (OMP) [16]. The algorithm is based on the geometry of the polar polytope where at each step a basis function is chosen by finding the maximal vertex using a path-following method. The algorithmic comp...
Sparsity Adaptive Matching Pursuit Detection Algorithm Based on Compressed Sensing for Radar Signals
In this paper, the application of the emerging compressed sensing (CS) theory and the geometric characteristics of the targets in radar images are investigated. Currently, the signal detection algorithms based on the CS theory require knowing the prior knowledge of the sparsity of target signals. However, in practice, it is often impossible to know the sparsity in advance. To solve this problem...
to discuss my point, i have collected quite a number of articles, anthologies, and books about "wuthering heights" applying various ideas and theories to this fantastic story. hence, i have come to believe that gadamer and jauss are rightful when they claim that "the individaul human mind is the center and origin of all meaning," 3 that reading literature is a reader-oriented activity, that it ...
due to the limiting workspace of parallel manipulator and regarding to finding the trajectory planning of singularity free at workspace is difficult, so finding a best solution that can develop a technique to determine the singularity-free zones in the workspace of parallel manipulators is highly important. in this thesis a simple and new technique are presented to determine the maximal singula...
a one dimensional dynamic model for a riser reactor in a fluidized bed catalytic cracking unit (fccu) for gasoil feed has been developed in two distinct conditions, one for industrial fccu and another for fccu using various frequencies of microwave energy spaced at the height of the riser reactor (fccu-mw). in addition, in order to increase the accuracy of component and bulk diffusion, instanta...
We introduce a new greedy algorithm to find approximate sparse representations s of x = As by finding the Basis Pursuit (BP) solution of the linear program min{‖s‖ 1 | x = As}. The proposed algorithm is based on the geometry of the polar polytope P ∗ = {c | à c ≤ 1} where à = [A,−A] and searches for the vertex c ∈ P ∗ which maximizes x c using a path following method. The resulting algorithm is...
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