Blind signal separation
Encyclopedia
Blind signal separation, also known as blind source separation, is the separation of a set of signals
from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process.
Blind signal separation relies on the assumption that the source signals do not correlate with each other. For example, the signals may be mutually statistically independent or decorrelated. Blind signal separation thus separates a set of signals into a set of other signals, such that the regularity of each resulting signal is maximized, and the regularity between the signals is minimized (i.e. statistical independence is maximized).
Because temporal redundancies (statistical regularities in the time domain) are "clumped" in this way into the resulting signals, the resulting signals can be more effectively deconvolved
than the original signals.
There are different methods of blind signal separation:
Signal processing
Signal processing is an area of systems engineering, electrical engineering and applied mathematics that deals with operations on or analysis of signals, in either discrete or continuous time...
from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process.
Blind signal separation relies on the assumption that the source signals do not correlate with each other. For example, the signals may be mutually statistically independent or decorrelated. Blind signal separation thus separates a set of signals into a set of other signals, such that the regularity of each resulting signal is maximized, and the regularity between the signals is minimized (i.e. statistical independence is maximized).
Because temporal redundancies (statistical regularities in the time domain) are "clumped" in this way into the resulting signals, the resulting signals can be more effectively deconvolved
Deconvolution
In mathematics, deconvolution is an algorithm-based process used to reverse the effects of convolution on recorded data. The concept of deconvolution is widely used in the techniques of signal processing and image processing...
than the original signals.
There are different methods of blind signal separation:
- Principal components analysisPrincipal components analysisPrincipal component analysis is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of uncorrelated variables called principal components. The number of principal components is less than or equal to...
- Singular value decompositionSingular value decompositionIn linear algebra, the singular value decomposition is a factorization of a real or complex matrix, with many useful applications in signal processing and statistics....
- Independent component analysisIndependent component analysisIndependent component analysis is a computational method for separating a multivariate signal into additive subcomponents supposing the mutual statistical independence of the non-Gaussian source signals...
- Dependent component analysis
- Non-negative matrix factorization
- Low-Complexity Coding and Decoding
- Stationary Subspace AnalysisStationary subspace analysisStationary Subspace Analysis is a blind source separation algorithm which factorizes a multivariate time series into stationary and non-stationary components.- Introduction :...
See also
- Factorial codeFactorial codeMost real world data sets consist of data vectors whose individual components are not statistically independent, that is, they are redundant in the statistical sense. Then it is desirable to create a factorial code of the data, i...
s - Source separationSource separationSource separation problems in digital signal processing are those in which several signals have been mixed together and the objective is to find out what the original signals were. The classical example is the "cocktail party problem", where a number of people are talking simultaneously in a room ,...
- DeconvolutionDeconvolutionIn mathematics, deconvolution is an algorithm-based process used to reverse the effects of convolution on recorded data. The concept of deconvolution is widely used in the techniques of signal processing and image processing...
- Infomax principle
- Adaptive filtering