搜索结果: 1-13 共查到“应用数学 sparse”相关记录13条 . 查询时间(0.031 秒)
GENERALIZED SPARSE SIGNAL MIXING MODEL AND APPLICATION TO NOISY BLIND SOURCE SEPARATION
GENERALIZED SPARSE SIGNAL MIXING MODEL NOISY BLIND SOURCE SEPARATION
2015/9/29
Sparse constraints on signal decompositions are justified bytypical sensor data used in a variety of signal processing fields such as acoustics, medical imaging, or wireless, but moreover can lead to ...
Convolutive Demixing with Sparse Discrete Prior Models for Markov Sources
Convolutive Demixing Sparse Discrete Prior Models Markov Sources
2015/9/29
In this paper we present a new source separation method based on dynamic sparse source signal models. Source signals are modeled in frequency domain as a product of a Bernoulli selection variable with...
SOURCE SEPARATION USING SPARSE DISCRETE PRIOR MODELS
SOURCE SEPARATION SPARSE DISCRETE PRIOR MODELS
2015/9/29
In this paper we present a new source separation method based on dynamic sparse source signal models. Source signals are modeled in frequency domain as a product of a Bernoulli selection variablewith ...
Estimator for Number of Sources using Minimum Description Length Criterion for Blind Sparse Source Mixtures
Minimum Description Length Criterion Blind Sparse Source Mixtures
2015/9/29
In this paper I present a Minimum Description Length Estimator for number of sources in an anechoic mixture of sparse signals.The criterion is roughly equal to the sum of negative normalized maximum l...
OPTIMAL BEAM PATTERN DESIGN FOR VERY LARGE SENSOR ARRAYS WITH SPARSE SAMPLING
OPTIMAL BEAM PATTERN DESIGN VERY LARGE SENSOR ARRAYS SPARSE SAMPLING
2015/9/29
Consider a large scale sensor array having N sensors that monitors a surveillance area. Using all sensors simultaneously may be unreasonable in terms of power consumption and data processing.For examp...
SPARSE FOURIER TRANSFORM VIA BUTTERFLY ALGORITHM
Fourier transform butterfly algorithm multiscale methods far field pattern
2015/7/14
This paper introduces a fast algorithm for computing sparse Fourier transforms with spatial and Fourier data supported on curves or surfaces. This problem appears naturally in several important applic...
A FAST PARALLEL ALGORITHM FOR SELECTED INVERSION OF STRUCTURED SPARSE MATRICES WITH APPLICATION TO 2D ELECTRONIC STRUCTURE CALCULATIONS
selected inversion parallel algorithm electronic structure calculation
2015/7/14
An efficient parallel algorithm is presented for computing selected components of A−1 where A is a structured symmetric sparse matrix. Calculations of this type are useful for several applicatio...
The Curvelet Representation of Wave Propagators is Optimally Sparse
Curvelet Representation Wave Propagators Optimally Sparse
2015/6/17
This paper argues that curvelets provide a powerful tool for representing very general linear symmetric systems of hyperbolic differential equations. Curvelets are a recently developed multiscale syst...
Safe Feature Elimination in Sparse Supervised Learning
Sparse classi cation sparse regression LASSO feature elimination
2010/12/16
We investigate fast methods that allow to quickly eliminate variables (features) in supervised
learning problems involving a convex loss function and a l1-norm penalty, leading to a potentially subst...
Extremal Sparse Polynomial Systems Over Local Fields
Extremal Sparse Polynomial Systems Local Fields
2010/11/23
Consider a system F of n polynomials in n variables, with a total of n+k distinct exponent vectors, over any local field L of characteristic 0. We discuss conjecturally tight upper and lower bounds o...
We study Maker/Breaker games on the edges of sparse graphs. Maker and Breaker take turns in claiming previously unclaimed edges of a given graph H. Maker aims to occupy a given target graph G and Bre...
Singular continuous spectrum of one-dimensional Schrödinger operator with point interactions on a sparse set
Singular continuous spectrum one-dimensional Schrö dinger operator
2010/11/18
We say that a discrete set $X =\{x_n\}_{n\in\dN_0}$ on the half-line $$0=x_0 < x_1 sparse in the case the distances $\Delta x_n = x_{n+1} -x_n$ between neighboring p...
Free energy computations by minimization of Kullback-Leibler divergence: an efficient adaptive biasing potential method for sparse representations
Free energy Kullback-Leibler divergence
2010/11/17
The present paper proposes an adaptive biasing potential for the computation of free energy landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecula...