- Linear predictive analysis
Linear predictive analysis can be thought of as a simple form of first-order
extrapolation: if it has been changing at this rate then it will probably continue to change at approximately the same rate, at least in the short term. This is equivalent to fitting a tangentto the graph and extending the line.
One use of this is in
Linear predictive codingwhich can be used as a method of reducing the amount of data needed to approximately encodea series. Suppose it is desired to store or transmit a series of values representing voice. The value at each sampling point could be transmitted (if 256 values are possible then 8 bits of data for each point are required, if the precision of 65536 levels are desired then 16 bits per sample are required). If it is known that the value rarely changes more than +/- 15 values between successive samples (-15 to +15 is 31 steps, counting the zero) then we could encode the change in 5 bits. As long as the change is less than +/- 15 values in successive steps the value will exactly reproduce the desired sequence. When the rate of change exceeds +/-15 then the reconstructed values will temporarily differ from the desired value; provided fast changes that exceed the limit are rare it may be acceptable to use the approximation in order to attain the improved coding density.
Wikimedia Foundation. 2010.
См. также в других словарях:
Linear predictive coding — (LPC) is a tool used mostly in audio signal processing and speech processing for representing the spectral envelope of a digital signal of speech in compressed form, using the information of a linear predictive model. It is one of the most… … Wikipedia
Linear Predictive Coding — (LPC) ist ein in der Audio Signalverarbeitung und Sprachverarbeitung unter anderem für die Audiodatenkompression und Sprachanalyse verwendetes Verfahren, das mittels Audiosynthese arbeitet. Dabei wird der Stimmtrakt (des Menschen) modellhaft… … Deutsch Wikipedia
Predictive analytics — encompasses a variety of techniques from statistics and data mining that analyze current and historical data to make predictions about future events. Such predictions rarely take the form of absolute statements, and are more likely to be… … Wikipedia
Linear prediction — is a mathematical operation where future values of a discrete time signal are estimated as a linear function of previous samples.In digital signal processing, linear prediction is often called linear predictive coding (LPC) and can thus be viewed … Wikipedia
Linear regression — Example of simple linear regression, which has one independent variable In statistics, linear regression is an approach to modeling the relationship between a scalar variable y and one or more explanatory variables denoted X. The case of one… … Wikipedia
List of numerical analysis topics — This is a list of numerical analysis topics, by Wikipedia page. Contents 1 General 2 Error 3 Elementary and special functions 4 Numerical linear algebra … Wikipedia
Technical analysis — Financial markets Public market Exchange Securities Bond market Fixed income Corporate bond Government bond Municipal bond … Wikipedia
Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… … Wikipedia
Optimal discriminant analysis — (ODA) and the related classification tree analysis (CTA) are statistical methods that maximize predictive accuracy. For any specific sample and exploratory or confirmatory hypothesis, optimal discriminant analysis (ODA) identifies the statistical … Wikipedia
Principal components analysis — Principal component analysis (PCA) is a vector space transform often used to reduce multidimensional data sets to lower dimensions for analysis. Depending on the field of application, it is also named the discrete Karhunen Loève transform (KLT),… … Wikipedia