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	Linear prediction - Wikipedia, the free encyclopedia
		Linear prediction is a mathematical operation where future values of a digital 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 as a subset of filter theory.
		In system analysis (a subfield of mathematics), linear prediction can be viewed as a part of mathematical modelling or optimization.
	en.wikipedia.org /wiki/Linear_prediction (413 words)

	Linear predictive coding - Wikipedia, the free encyclopedia
		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 powerful speech analysis techniques, and one of the most useful methods for encoding good quality speech at a low bit rate and provides extremely accurate estimates of speech parameters.
		Transmission of the filter coefficients directly (see linear prediction for definition of coefficients) is undesirable, since they are very sensitive to errors.
	en.wikipedia.org /wiki/Linear_predictive_coding (552 words)

	Wide dynamic range analog-to-digital converter using linear prediction - Patent 4792787
		The recirculated predicted signal is converted to analog form (unless predicted via analog means) and subtracted from the analog input signal to provide an error signal output digitized to form low order bits that correspond in time with an output of high order bits generated by a digitized prediction signal.
		Prediction techniques based on the normal equations using the past N data samples unfortunately require a number of arithmetic operations on the order of N.sup.2, O(N.sup.2), even when fast algorithms such as Durbin's Method are used to solve the normal equations.
		A particularly attractive high speed approach to linear prediction is to use the fixed-weight filter techniques of Brown and Splettstosser, supra, implemented using the systolic transversal filters of H. Kung.
	www.freepatentsonline.com /4792787.html (4509 words)

	Linear prediction - Patent Storm (Site not responding. Last check: 2007-11-07)
		Disclosed is a voice encoding method having a synthesis filter implemented using linear prediction coefficients obtained by dividing an input signal into frames each of a fixed length, and subjecting the input signal to linear prediction analysis in the frame units, generating a reconstructed...
		A linear prediction coefficient is generated by subjecting the reference speech signal to a linear prediction analysis.
		Linear prediction coefficients are derived from the input acoustic signal in a linear prediction coding analysis part, and the prediction coefficients are subjected to...
	www.patentstorm.us /class/704/262-Linear_prediction.html (3616 words)

	Code excited linear prediction coder with a short-length codebook for modeling speech having local peak - Patent 5699483 (Site not responding. Last check: 2007-11-07)
		linear prediction analyzing means for analyzing the current input speech signal and a past input speech signal preceding to the current input speech signal to calculate a plurality of linear prediction coefficients, the predicted input speech signal used in the prediction residual signal calculating means being predicted by using the linear prediction coefficients.
		1, in the linear prediction analyzing unit 13, a plurality of linear prediction coefficients.alpha.i (i=1 to p) are generated in advance from a plurality of samples of past and current input speech signals Sin to use the linear prediction coefficients for the prediction of the current input speech signal Sin.
		In the predicted residual signal calculating unit 33, a predicted residual signal is calculated by using the linear prediction coefficients generated by the linear prediction analyzing unit 13 and the current input speech signal Sin.
	www.freepatentsonline.com /5699483.html (5355 words)

	Prediction
		Prediction of future events is an ancient human wish.
		However, the desire to make predictions remains as strong as ever, and is an important part of almost every aspect of human life.
		Thus the element of surprise in a scientific result is essential, because the risk in the prediction is unavoidable.
	www.brainyencyclopedia.com /encyclopedia/p/pr/prediction.html (426 words)

	NMR NOTES #9
		Linear prediction is a software processing tool that examines a periodic function, such as an NMR free induction decay, extracts a set of coefficients, and extrapolates, either forward or backward to predict what the data would have done had it been collected.
		Linear prediction parameters are added to a data set with the parlp command.
		In order to perform a linear prediction calculation, it is necessary to calculate a set of coefficients describing the frequencies present.
	www.chem.tamu.edu /services/NMR/notes/notes_13.htm (771 words)

	Speech compression technique (Site not responding. Last check: 2007-11-07)
		Thus, for a pitch-excited LPC vocoder, the output of the analysis stage would be the linear predictive parameters of the vocal tract filter, the state of the voiced/unvoiced switch, the pitch period(if voiced), and the excitation gain.
		Linear predictive coding is one of the most popular coding techniques for speech signals and it has received extensive attention over the past two decades.
		Pitch-excited linear predictive coders also have advantage that they are able to operate at bit rates using relatively modest computational resources while providing a very usable coded representation of the original speech signal.
	murray.newcastle.edu.au /users/staff/iw/Projects/1998/Yap/speech.html (2381 words)

	Method and apparatus for applying linear prediction to critical band subbands of split-band perceptual coding systems - ... (Site not responding. Last check: 2007-11-07)
		The quantizers for the prediction errors are reinitialized whenever a sharp transient in the signal is encountered.
		Linear predictor 340 adapts predictive filter coefficients in response to quantized prediction errors received from path 306 and generates along path 305 prediction values in response to recovered replicas received from path 307.
		Linear predictor 840 adapts predictive filter coefficients in response to quantized prediction errors received from path 806 and generates along path 805 predicted values in response to recovered replicas received from path 807.
	www.freepatentsonline.com /5699484.html (9089 words)

	Linear Prediction (Site not responding. Last check: 2007-11-07)
		Forward prediction is used to predict data out to twice the actual acquisition time, and is used with severely truncated data, such as in the indirect dimension of 2D experiments as an alternative to zero-filling.
		For backward prediction (which is the default), the user must set the number of points to back predict, the number of data points upon which to base the prediction and the number of frequencies to predict.
		The number of data points on which the prediction is based must be less than half the total number of data points, or the algorithm fails.
	www.acornnmr.com /NutsHelp/LN.html (376 words)

	ESS 265: Chapter 9/Linear Prediction Filters and Neural Networks
		Linear prediction filters are used to describe the relation of one output, or system variable, to one or more inputs.
		If we consider that an interpolated point is actually a combination (linear or otherwise) of its neighbors, we can see how this would cause a linear prediction filter to be unable to resolve the different influence of that point and its neighbors.
		Coefficient versus lag for three moving average linear prediction filters: one in which the time series showed exponential decay; one in which the time series showed recurrence; and one in which the output was controlled by the derivative of the input.
	www-ssc.igpp.ucla.edu /personnel/russell/ESS265/Ch9/linear_predict (5247 words)

	Linear Prediction (Site not responding. Last check: 2007-11-07)
		A common approach to estimating the time-varying resonances of the vocal tract from recorded voice signals is with linear prediction.
		In this analysis, the composite spectral properties of the radiation, vocal tract, and glottal excitation are represented by an all-pole time-varying digital filter of the form
		A linear predictor, represented by the block diagram of Fig.
	www.music.mcgill.ca /~gary/614/week11/node15.html (279 words)

	Linear Prediction (Site not responding. Last check: 2007-11-07)
		Linear prediction is a method to construct FID points, which have been truncated.
		The other useful application of linear predicting FID points is in the beginning of the signal.
		The macro "lpbc" will delete the first points of your NMR signal, linear predict what these points should be and Fourier transform your spectrum.
	nmr.chem.indiana.edu /NMRguide/process/Linear_Prediction.html (348 words)

	THE USE OF LINEAR PREDICTION OF SPEECH IN COMPUTER MUSIC APPLICATIONS
		Linear prediction is a method of designing a filter to best approximate, in a mean squared error sense, the spectrum of a given signal.
		The error signal of a 4th to 6th order linear prediction process is usually sufficiently whitened to improve the intelligibility greatly, but at the expense of the clarity of the original musical source.
		With the autocorrelation method of linear prediction, the error energy is easily obtained as an automatic result of the filter computation.
	members.tripod.com /werdav/jamoorer.html (5768 words)

	[No title] (Site not responding. Last check: 2007-11-07)
		For another description of use: Using linear prediction (from Texas AMU) Linear prediction should not be used recklessly because you can create artifacts.
		Linear prediction can be used to predict forward or backward and will not fix grossly undersampled data.
		The standard setup will be for backward prediction of the first point in the np dimension and for forward prediction in the ni dimension to correction for truncation.
	www1.umn.edu /nmr/news/lp.html (221 words)

	Linear Prediction
		On each iteration the mean squared value of the prediction residual is calculated and this is used to compute the expected number of bits needed to code the residual signal.
		Whilst it is possible to construct signals that defeat this search procedure, in practice for speech signals it has been found that the occasional use of a lower prediction order results in an insignificant increase in the bit rate and has the additional side effect of requiring less compute to decode.
		Moreover, as the sum of absolute values is linearly related to the variance, this may be used as the basis of predictor selection and so the whole process is cheap to compute as it involves no multiplications.
	svr-www.eng.cam.ac.uk /~ajr/tr156/node5.html (475 words)

	Linear Prediction (Site not responding. Last check: 2007-11-07)
		In linear prediction, one uses ancestors (or previous samples) to predict where subsequent values will be.
		Prediction parameters are computed (based upon a given number of ancestors), and from there on can then compute the error between actual and predicted position to gain values of smaller magnitude, which can then be compressed.
		We obtained good results using linear prediction, mainly when the vertex positions were quantized and rounded before linear prediction took place.
	meru.cecs.missouri.edu /mvl/cmesh/lp.html (426 words)

	[No title]
		Linear prediction models the vocal tract by a time varying all pole model and manages to remove a lot of redundancy in the speech signal.
		Stationarity of the Speech Signal As linear prediction analysis assumes that the input signal is Wide Sense Stationary (WSS), we must partition the speech signal into frames short enough so that the WSS assumption is more or less true, yet long enough to be efficient for coding purposes.
		Linear Predictive Model The human vocal system can be modeled quite accurately as an excitation generator feeding a concatenation of acoustic tubes with varying cross sectional areas.
	www.ee.umd.edu /courses/enee624.F2002/report1.doc (4278 words)

	Forward Linear Prediction (Site not responding. Last check: 2007-11-07)
		As an alternative, we can use Linear Prediction to generate additional data points and then apply a window function which acts mostly upon these predicted points to bring the end of the FID to zero, preserving the real data points.
		The first item, number of points for back prediction, is irrelevant for the present case of forward prediction.
		This is the same FID as above after forward linear prediction to double the number of points and then application of a cosine squared window function.
	www.acornnmr.com /NutsHelp/LN_F_show.html (333 words)

	Speech Processing Using Linear Prediction
		The error in the prediction, e(n), is the difference between the what is being predicted and the prediction.
		Intuitively, linear prediction exploits the fact that a new sample of a signal is not totally independent of previous samples, usually.
		In fact, for speech, the linear predictor has to constantly change to adapt to what is being said.
	ptolemy.eecs.berkeley.edu /eecs20/speech/lp.html (1159 words)

	Linear Prediction analysis (Site not responding. Last check: 2007-11-07)
		Linear prediction analysis of speech is historically one of the most important speech analysis techniques.
		The basis is the source-filter model where the filter is constrained to be an all-pole linear filter.
		This amounts to performing a linear prediction of the next sample as a weighted sum of past samples:
	svr-www.eng.cam.ac.uk /~ajr/SA95/node38.html (78 words)

	3.4.3 High-dimensional Empirical Linear Prediction
		Applying a traditional multivariate linear model, one can incorporate a small number of the elements of the observation with a known design matrix to predict the rest of the elements.
		We investigate an empirical linear model, in which we allow ourselves to use the data to determine the size of the design matrix and to estimate the unknown part of the design matrix.
		As an example, for a 13 bit A/D converter, to be absolutely sureof performance, one needs to test 8192 outputs, corresponding to transition levels (usually voltage levels) for the conversion of the analog signals to the digital signals.
	www.itl.nist.gov /div898/pubs/ar/ar1998/node38.html (270 words)

	Linear prediction -- Facts, Info, and Encyclopedia article (Site not responding. Last check: 2007-11-07)
		Linear prediction is a mathematical operation where future values of a (Click link for more info and facts about digital) digital (Any communication that encodes a message) signal are estimated as a (Click link for more info and facts about linear function) linear function of previous samples.
		where is the predicted signal value, the previous observed values, and the predictor coefficients.
		The differences are found in the way the parameters are chosen.
	www.absoluteastronomy.com /encyclopedia/l/li/linear_prediction.htm (526 words)

	Locally linear prediction (Site not responding. Last check: 2007-11-07)
		Locally linear approximation was introduced in [45, 46].
		There are of course artefacts due to noise and the roughness of this approach, but there are good reasons to assume that the line-like substructure reflects fractality of the unperturbed system.
		Casdagli [53] suggested to use local linear models as a test for nonlinearity: He computed the average forecast error as a function of the neighborhood size on which the fit for
	www.new.ox.ac.uk /~nmcgroga/work/tisean/Docs/node20.html (475 words)

	Prediction of Rates of Inbreeding in Populations Selected on Best Linear Unbiased Prediction of Breeding Value -- Bijma ...
		Prediction of Rates of Inbreeding in Populations Selected on Best Linear Unbiased Prediction of Breeding Value
		Prediction errors (%) of rates of inbreeding from an extension of Burrow's method for a population with 20 sires
		In the present prediction, the first term of Equation 1 was
	www.genetics.org /cgi/content/full/156/1/361 (4287 words)

	Optimization of Chromatographic Solvent Gradients using a Non-linear Prediction Model
		Typically this prediction has been based on the theory that the logarithm of the retention factor is inversely proportional to the mobile phase strength.
		Accuracy of these predictions has generally been reasonable for most samples, and chromatographers have typically been willing to accept the results due to the necessity of performing (and interpreting) more test runs prior to applying more complex models.
		Non-linear prediction has been applied to a number of samples that were not modeled well by linear prediction.
	www.acdlabs.com /publish/publ03/p03_nonlin.html (254 words)

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