نتایج جستجو برای: multidimensional signal processing
تعداد نتایج: 854967 فیلتر نتایج به سال:
Abstract- Suppressing clutter is one of the most crucial phases in radar signal processing. Also, Blind Source Separation (BSS) is one of the recent and very important problems in signal processing that shows its efficiency in many applications. Degenerate Unmixin Estimation Technique (DUET) is one of the Underdetermined BSS algorithms that separate sources from mixtures using only two mixtures...
Processing multichannel signals using digital signal processing techniques has received increased attention lately due to its importance in applications such as multimedia technologies and telecommunications. The objective of this paper is twofold: 1) to introduce adaptive filtering techniques to the reader who is just beginning in this area and 2) to provide a review for the reader who may be ...
Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both doma...
The suitability of methods from multidimensional systems theory and digital signal processing for the e cient simulation of time and space dependent problems has already been demonstrated. Properly chosen functional transformations for the time and space coordinates turn a partial di erential equation into a transfer function description of a multidimensional continuous system. It serves as the...
Nonnegative Tensor Factorization (NTF) is an emerging technique in multidimensional signal analysis and it can be used to find partsbased representations of high-dimensional data. Inmany applications such as multichannel spectrogram processing or multiarray spectra analysis, the unknown features have locally smooth temporal or spatial structure. In this paper, we incorporate to an objective fun...
Title of dissertation: TENSOR COMPLETION FOR MULTIDIMENSIONAL INVERSE PROBLEMS WITH APPLICATIONS TO MAGNETIC RESONANCE RELAXOMETRY Ariel Hafftka, Doctor of Philosophy, 2016 Dissertation directed by: Professor Wojciech Czaja Department of Mathematics This thesis deals with tensor completion for the solution of multidimensional inverse problems. We study the problem of reconstructing an approxima...
Multidimensional signal detection theory is a multivariate extension of signal detection theory that makes two fundamental assumptions, namely that every mental state is noisy and that every action requires a decision. The most widely studied version is known as general recognition theory (GRT). General recognition theory assumes that the percept on each trial can be modeled as a random sample ...
This is a special issue published in volume 2003 of " EURASIP Journal on Applied Signal Processing. " All articles are open access articles distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Recent years have seen the emergence of a variety of new multimedia (text...
In general, linearity is assumed to hold in multivariate calibration (MVC), but this may not be true. We approach the MVC problem using multidimensional penalized signal regression, which can be extended with an explicit link function between linear prediction and response and in the spirit of single-index models. As the twodimensional surface of calibration coefficients is smoothly and general...
Faustine is the first interpreter for the digital audio signal processing language Faust and its vector extension. This domainspecific language for sample-based audio is highly expressive and can be efficiently compiled. Faustine has been designed and implemented, in OCaml, to validate the Faust multirate vector extension proposed in the literature, without having to modify the sophisticated Fa...
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