Results 81 to 90 of about 37,640 (313)
Signal Subspace Speech Enhancement with Oblique Projection and Normalization [PDF]
Radioengineering, 2017 In this paper, a subspace speech enhancement method handling colored noise using oblique projection is proposed. Perceptual features and variance normalization are used to reduce residual noise and improve speech intelligibility of the output. Initially,
S. Surendran, T. K. Kumar
doaj
Sparse signal subspace decomposition based on adaptive over-complete dictionary
EURASIP Journal on Image and Video Processing, 2017 This paper proposes a subspace decomposition method based on an over-complete dictionary in sparse representation, called “sparse signal subspace decomposition” (or 3SD) method. This method makes use of a novel criterion based on the occurrence frequency
Hong Sun +2 more
doaj +1 more source
Advanced Intelligent Discovery, EarlyView.This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley +1 more source
Millimeter Wave Channel Estimation Based on Subspace Fitting
IEEE Access, 2018 We consider the channel estimation of millimeter wave (mmWave) multiple-input multiple-output systems, where both the transmitter and receiver adopt hybrid beamforming structure.
Didi Zhang +3 more
doaj +1 more source
Order estimation for subspace methods
Automatica, 2001 The author proposes three methods for order estimation in the context of subspace methods. Two of them, both in the cases with observed inputs and without exogenous inputs, are based on the information contained in the estimated singular values (SV) and lower bounds on the (subjective) penalty term in order for the estimates to be (strongly) consistent.
openaire +4 more sources
Forecasting linear dynamical systems using subspace methods [PDF]
A new procedure to predict with subspace methods is presented in this paper. It is based on combining multiple forecasts obtained from setting a range of values for a specic parameter that is typically xed by the user in the subspace methods literature ...
Alfredo García-Hiernaux
core
Evaluation and Selection of Models for Motion Segmentation
, 2001 We first present an improvement of Kanatani's subspace separation [8] for motion segmentation by newly introducing the affine space constraint. We point out that this improvement does not always fare well due to the effective noise it introduces.
Kenichi Kanatani, Kanatani, Kenichi
core +1 more source
Transformation invariance in hand shape recognition [PDF]
, 2006 In hand shape recognition, transformation invariance is key for successful recognition. We propose a system that is invariant to small scale, translation and shape variations.
T. Coogan +3 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez +4 more
wiley +1 more source
Unit Roots and Cointegrating Matrix Estimation using Subspace Methods [PDF]
We propose a new procedure to detect unit roots based on subspace methods. It has three main original features. First, the same method can be applied to single or multiple time series.
José Casals +2 more
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