- Blind signal separation
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 are non-redundant. For example, the signals may be mutually
statistically independentor 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:
Principal components analysis
Singular value decomposition
Independent component analysis
Dependent component analysis
Non-negative matrix factorization
Low-Complexity Coding and Decoding
* [http://visl.technion.ac.il/demos/bss Blind source separation flash presentation]
Wikimedia Foundation. 2010.
Look at other dictionaries:
Methode de separation aveugle de source — Méthode de séparation aveugle de source La séparation aveugle de source (SAS) consiste à estimer un jeu de N sources inconnues à partir d un jeu de P observations. Ces observations sont des mélanges de ces sources et proviennent de capteurs… … Wikipédia en Français
Méthode De Séparation Aveugle De Source — La séparation aveugle de source (SAS) consiste à estimer un jeu de N sources inconnues à partir d un jeu de P observations. Ces observations sont des mélanges de ces sources et proviennent de capteurs (antennes, microphones, caméras par exemple) … Wikipédia en Français
Méthode de séparation aveugle de source — La séparation aveugle de source (SAS) consiste à estimer un jeu de N sources inconnues à partir d un jeu de P observations. Ces observations sont des mélanges de ces sources et proviennent de capteurs (antennes, microphones, caméras par exemple) … Wikipédia en Français
Source 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… … Wikipedia
Window blind — For other uses, see Blinds (disambiguation). For the desktop theming software, see WindowBlinds. Various window blinds A window blind is a type of window coverings. There are many different kinds of window blinds, using different systems and… … Wikipedia
Independent component analysis — (ICA) is a computational method for separating a multivariate signal into additive subcomponents supposing the mutual statistical independence of the non Gaussian source signals. It is a special case of blind source separation. Definition When… … Wikipedia
Computational auditory scene analysis — (CASA) is the study of auditory scene analysis by computational means . In essence, CASA systems are machine listening systems that aim to separate mixtures of sound sources in the same way that human listeners do. CASA differs from the field… … Wikipedia
Self-modeling mixture analysis — is a class of data analysis techniques that are also termed as Blind signal separation or Blind source separation which are used to separate pure data components from additive mixture data. Contents 1 Examples 2 Multivariate curve resolution 3… … Wikipedia
Empirical orthogonal functions — In statistics and signal processing, the method of empirical orthogonal function (EOF) analysis is a decomposition of a signal or data set in terms of orthogonal basis functions which are determined from the data. It is the same as performing a… … Wikipedia
Hilbert spectrum — The Hilbert spectrum (sometimes referred to as the Hilbert amplitude spectrum ) is a statistical tool that can help in distinguishing among a mixture of moving signals. The spectrum itself is decomposed into its component sources using… … Wikipedia