signal+subspace

См. также в других словарях:

• Signal subspace — In signal processing, signal subspace methods are empirical linear methods for dimensionality reduction and noise reduction. These approaches have attracted significant interest and investigation recently in the context of speech enhancement,… …   Wikipedia

• 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. Signals of interest can include sound, images, time varying measurement …   Wikipedia

• Signal reconstruction — In signal processing, reconstruction usually means the determination of an original continuous signal from a sequence of equally spaced samples.This article takes a generalized abstract mathematical approach to signal sampling and reconstruction …   Wikipedia

• Multiple signal classification — MUSIC redirects here. For other uses, see Music (disambiguation). MUltiple SIgnal Classification (MUSIC) is an algorithm used for frequency estimation[1] and emitter location.[2] Contents 1 MUSIC algorithm …   Wikipedia

• Frequency estimation — This article is about the technique in signal processing. The term frequency estimation can also refer to probability estimation. Frequency estimation is the process of estimating the complex frequency components of a signal in the presence of… …   Wikipedia

• Noise reduction — For sound proofing, see soundproofing. For scientific aspects of noise reduction of machinery and products, see noise control. Noise reduction is the process of removing noise from a signal. All recording devices, both analogue or digital, have… …   Wikipedia

• Dimension reduction — For dimensional reduction in physics, see Dimensional reduction. In machine learning, dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature… …   Wikipedia

• Wavelet — A wavelet is a mathematical function used to divide a given function or continuous time signal into different frequency components and study each component with a resolution that matches its scale. A wavelet transform is the representation of a… …   Wikipedia

• Orthogonality principle — In statistics and signal processing, the orthogonality principle is a necessary and sufficient condition for the optimality of a Bayesian estimator. Loosely stated, the orthogonality principle says that the error vector of the optimal estimator… …   Wikipedia

• Vector space — This article is about linear (vector) spaces. For the structure in incidence geometry, see Linear space (geometry). Vector addition and scalar multiplication: a vector v (blue) is added to another vector w (red, upper illustration). Below, w is… …   Wikipedia

• Intrinsic dimension — In signal processing of multidimensional signals, for example in computer vision, the intrinsic dimension of the signal describes how many variables are needed to represent the signal. For a signal of N variables, its intrinsic dimension M… …   Wikipedia