搜索结果: 1-10 共查到“blind source separation”相关记录10条 . 查询时间(0.114 秒)
Blind Source Separation from Single Measurements using Singular Spectrum Analysis
side-channel analysis signal processing filtering
2016/3/23
Singular Spectrum Analysis (SSA) is a powerful data decomposition/recomposition technique that can be used to reduce the noise in time series. Compared to existing solutions aiming at similar purposes...
REAL-TIME TIME-FREQUENCY BASED BLIND SOURCE SEPARATION
REAL-TIME TIME-FREQUENCY BLIND SOURCE SEPARATION
2015/9/29
We present a real-time version of the DUET algorithm forthe blind separation of any number of sources using only two mixtures. The method applies when sources are Wdisjoint orthogonal, that is, when t...
BLIND SOURCE SEPARATION BASED ON SPACE-TIME-FREQUENCY DIVERSITY
BLIND SOURCE SEPARATION SPACE-TIME-FREQUENCY DIVERSITY
2015/9/29
We investigate the assumption that sources have disjoint support in the time domain, time-frequency domain, or frequency domain. We call such signals disjoint orthogonal. The class of signals that app...
SCALABLE NON-SQUARE BLIND SOURCE SEPARATION IN THE PRESENCE OF NOISE
SCALABLE NON-SQUARE SOURCE SEPARATION PRESENCE OF NOISE
2015/9/29
Few source separation and independent component analysis approaches attempt to deal with noisy data. Weconsider an additive noise mixing model with an arbitrary number of sensors and possibly more sou...
NON-SQUARE BLIND SOURCE SEPARATION UNDER COHERENT NOISE BY BEAMFORMING AND TIME-FREQUENCY MASKING
NON-SQUARE BLIND SOURCE SEPARATION COHERENT NOISE BY BEAMFORMING TIME-FREQUENCY MASKING
2015/9/29
To be applicable in realistic scenarios, blind source separation approaches should deal evenly with non-square cases and the presence of noise. We consider an additive noisemixing model with an arbitr...
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 ...
SEMI-BLIND SOURCE SEPARATION FOR ESTIMATION OF CLAY CONTENT OVER SEMI-VEGETATED AREAS,FROM VNIR/SWIR HYPERSPECTRAL AIRBORNE DATA
Hyperspectral remote sensing Semi-Blind source separation Non-Negative Matrix Factorization partial least squares regression clay content semi-vegetated pixels
2015/9/21
The applicability of Visible, Near-Infrared and Short Wave Infrared (VNIR/SWIR) hyperspectral imagery for soil property mapping decreases when surfaces are partially covered by vegetation. The objecti...
An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
slow feature analysis nonlinear blind source separation independent component analysis
2015/7/15
We present and test an extension of slow feature analysis as a novel approach to nonlinear blind source separation. The algorithm relies on temporal correlations and iteratively reconstructs a set of ...
Adaptive Parallel Computation for Blind Source Separation with Systolic Architecture
BSS convolutive mixtures VLSI field programmable gate array (FPGA)
2013/1/28
The purpose of Blind Source Separation (BSS) is to obtain separated sources from convolutive mixture inputs. Among the various available BSS methods, Independent Component Analysis (ICA) is one of the...
ADIS——A robust pursuit algorithm for probabilistic，constrained and non-square blind source separation with application to fMRI
ADIS robust pursuit algorithm blind source separation fMRI
2010/3/18
In this article, we develop an algorithm for probabilistic and constrained projection pursuit.
Our algorithm called ADIS (automated decomposition into sources) accepts arbitrary non-linear
contrast ...