Search Results - "HUSØY, John Hakon"

CPR artifact removal from human ECG using optimal multichannel filtering by Aase, S.O., Eftestol, T., Husoy, J.H., Sunde, K., Steen, P.A.

“…The purpose of this study was to assess whether the artifacts presented by precordial compressions during cardiopulmonary resuscitation could be removed from…”
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Family of iterative LS-based dictionary learning algorithms, ILS-DLA, for sparse signal representation by Engan, Kjersti, Skretting, Karl, Husøy, John Håkon

“…The use of overcomplete dictionaries, or frames, for sparse signal representation has been given considerable attention in recent years. The major challenges…”
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Selective partial update and set-membership subband adaptive filters by Abadi, Mohammad Shams Esfand, Husøy, John Håkon

“…This paper presents three efficient subband adaptive filter (SAF) algorithms featuring low computational complexity. In the first algorithm, which is called…”
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Predicting outcome of defibrillation by spectral characterization and nonparametric classification of ventricular fibrillation in patients with out-of-hospital cardiac arrest by EFTESTØL, Trygve, SUNDE, Kjetil, AASE, Sven Ole, HUSØY, John Hakon, STEEN, Petter Andreas

“…In 156 patients with out-of-hospital cardiac arrest of cardiac cause, we analyzed the ability of 4 spectral features of ventricular fibrillation before a total…”
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Diffusion LMS with communication constraints by Rortveit, O L, Husoy, John Häkon, Sayed, A H

“…Diffusion LMS is a distributed algorithm that allows a network of nodes to solve estimation problems in a fully distributed manner by relying solely on local…”
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Two improved multiband structured subband adaptive filter algorithms with reduced computational complexity by Shams Esfand Abadi, Mohammad, Husøy, John Håkon, Ahmadi, Mohammad Javad

“…•Establishment of the Family of IMSAF Algorithms:The SR-IMSAF and the DSR-IMSAF algorithms are established. These algorithms have the following features: (1)…”
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Filtering for texture classification: a comparative study by Randen, T., Husoy, J.H.

“…In this paper, we review most major filtering approaches to texture feature extraction and perform a comparative study. Filtering approaches included are Laws…”
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‘Probability of successful defibrillation’ as a monitor during CPR in out-of-hospital cardiac arrested patients by Eftestøl, Trygve, Sunde, Kjetil, Aase, Sven Ole, Husøy, John Håkon, Steen, Petter Andreas

“…The frequency spectrum of the ECG in ventricular fibrillation (VF) correlates with myocardial perfusion and might predict defibrillation success defined as…”
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Multi-frame compression: theory and design by Engan, Kjersti, Aase, Sven Ole, Husøy, John Håkon

“…This paper consist of two parts. The first part concerns approximation capabilities in using an overcomplete dictionary, a frame, for block coding. A frame…”
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On the application of a unified adaptive filter theory in the performance prediction of adaptive filter algorithms by Abadi, Mohammad Shams Esfand, Husøy, John Håkon

“…Employing a recently introduced unified adaptive filter theory, we show how the performance of a large number of important adaptive filter algorithms can be…”
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Mean-square performance of the family of adaptive filters with selective partial updates by Abadi, Mohammad Shams Esfand, Husøy, John Håkon

“…In this paper we present a general formalism for the family of adaptive filter algorithms with selective partial updates. Based on this, the mean-square…”
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Feasibility of shock advice analysis during CPR through removal of CPR artefacts from the human ECG by Eilevstjønn, Joar, Eftestøl, Trygve, Aase, Sven Ole, Myklebust, Helge, Husøy, John Håkon, Steen, Petter Andreas

“…Mechanical activity from chest compressions and ventilations during cardiopulmonary resuscitation (CPR) introduces artefact components into the…”
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Removal of cardiopulmonary resuscitation artifacts from human ECG using an efficient matching pursuit-like algorithm by Husoy, J.H., Eilevstjonn, J., Eftestol, T., Aase, S.O., Myklebust, H., Steen, P.A.

“…We present a computationally efficient and numerically robust solution to the problem of removing artifacts due to precordial compressions and ventilations…”
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Texture segmentation using filters with optimized energy separation by Randen, T., Husoy, J.H.

“…The design of filters for texture feature extraction is addressed. Based on a new feature extraction model, optimization approaches utilizing various feature…”
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General design algorithm for sparse frame expansions by Skretting, Karl, Husøy, John Håkon, Aase, Sven Ole

“…Signal expansions using frames may be considered as generalizations of signal representations based on transforms and filter banks. Frames, or dictionaries,…”
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On the selection and design of filter banks in normalised subband adaptive filters (NSAF) by Husoy, John Hakon

“…In this paper we reexamine a popular class of adaptive filter algorithms, namely the Normalised Subband Adaptive Filters (NSAF) whose superior convergence…”
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New insights into delayless subband adaptive filters by Husoy, John Hakon

“…The adaptive filter is an important workhorse of digital signal processing having a vast variety of applications in almost every branch of modern electronics…”
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Optimized signal expansions for sparse representation by Aase, S.O., Husoy, J.H., Skretting, J.H.H.K., Engan, K.

“…Traditional signal decompositions such as transforms, filterbanks, and wavelets generate signal expansions using the analysis-synthesis setting: the expansion…”
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Multichannel adaptive filtering using an efficient matching pursuit-like algorithm for removal of CPR artifacts in ECG signals by Eilevstjonn, Joar, Husoy, John Hakon, Ejtestol, Trygve, Aase, Sven Ole, Steen, Petter Andreas

“…In this contribution we present a novel algorithm for multichannel adaptive filtering. The algorithm is based on selective update of filter coefficients using…”
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Optimal filter-based detection of microcalcifications by Gulsrud, T.O., Husoy, J.H.

“…Deals with the problem of texture feature extraction in digital mammograms. The authors use the extracted features to discriminate between texture representing…”
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