Search results for "Linear prediction"
showing 10 items of 18 documents
A series expansion of the extended Debye-H�ckel equation and application to linear prediction of stability constants
1996
The Debye-Hückel semiempirical extended equation is frequently used to calculate activity coefficients of chemical species and equilibrium constants at ionic strengths different from those used in their experimental evaluation. A series expansion of the extended Debye-Hückel equation is proposed here and checked with experimental data taken from the literature. The expansion is linear in the ionic parameters and yields a geometrical series which converges rapidly and that enables the accurate calculation of interpolated and extrapolated activity coefficients and equilibrium constants by simple and multiple linear regression without previous knowledge of the ionic parameters.
k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation
2011
The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15. Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or …
Quantifying changes in EEG complexity induced by photic stimulation.
2009
Summary Objectives: This study aims to characterize EEG complexity, measured as the prediction error resulting from nonlinear prediction, in healthy humans during photic stimulation. Methods: EEGs were recorded from 15 subjects with eyes closed (EC) and eyes open (EO), during the baseline condition and during stroboscopic photic stimulation (PS) at 5, 10, and 15 Hz. The mean squared prediction error (MSPE) resulting from nearest neighbor local linear prediction was taken as complexity index. Complexity maps were generated interpolating the MSPE index over a schematic scalp representation. Results: Statistical analysis revealed that: i) EEG shows good predictability in all conditions and see…
Mixed predictability and cross-validation to assess non-linear Granger causality in short cardiovascular variability series
2006
A method to evaluate the direction and strength of causal interactions in bivariate cardiovascular and cardiorespiratory series is presented. The method is based on quantifying self and mixed predictability of the two series using nearest-neighbour local linear approximation. It returns two causal coupling indexes measuring the relative improvement in predictability along direct and reverse directions, and a directionality index indicating the preferential direction of interaction. The method was implemented through a cross-validation approach that allowed quantification of directionality without constraining the embedding of the series, and fully exploited the available data to maximise th…
Assessing Causality in normal and impaired short-term cardiovascular regulation via nonlinear prediction methods
2009
We investigated the ability of mutual nonlinear prediction methods to assess causal interactions in short-term cardiovascular variability during normal and impaired conditions. Directional interactions between heart period (RR interval of the ECG) and systolic arterial pressure (SAP) short-term variability series were quantified as the cross-predictability (CP) of one series given the other, and as the predictability improvement (PI) yielded by the inclusion of samples of one series into the prediction of the other series. Nonlinear prediction was performed through global approximation (GA), approximation with locally constant models (LA0) and approximation with locally linear models (LA1) …
Gaussian Process Sensitivity Analysis for Oceanic Chlorophyll Estimation
2017
Source at https://doi.org/10.1109/JSTARS.2016.2641583. Gaussian process regression (GPR) has experienced tremendous success in biophysical parameter retrieval in the past years. The GPR provides a full posterior predictive distribution so one can derive mean and variance predictive estimates, i.e., point-wise predictions and associated confidence intervals. GPR typically uses translation invariant covariances that make the prediction function very flexible and nonlinear. This, however, makes the relative relevance of the input features hardly accessible, unlike in linear prediction models. In this paper, we introduce the sensitivity analysis of the GPR predictive mean and variance functions…
Bivariate nonlinear prediction to quantify the strength of complex dynamical interactions in short-term cardiovascular variability.
2005
A nonlinear prediction method for investigating the dynamic interdependence between short length time series is presented. The method is a generalization to bivariate prediction of the univariate approach based on nearest neighbor local linear approximation. Given the input and output series x and y, the relationship between a pattern of samples of x and a synchronous sample of y was approximated with a linear polynomial whose coefficients were estimated from an equation system including the nearest neighbor patterns in x and the corresponding samples in y. To avoid overfitting and waste of data, the training and testing stages of the prediction were designed through a specific out-of-sampl…
Toll-quality digital secraphone
2002
This paper describes the design and performance of a secraphone that, when plugged between any conventional telephone set and the public telephone network, protects the speech information travelling through the PSTN. The device has a transparent operating mode that does not alter the signal and a secure mode, accessed upon request of any of the speakers, that encrypts the speech with digital techniques, assuring privacy against unwanted listeners. At the transmission branch, voice is sampled, coded with a CELP scheme at 9600 bps (with a slow mode at 7200 bps), encrypted with a proprietary algorithm and interfaced to the line with a V.32 modem chip set. The keys for encryption are establishe…
A simple joint estimation-detection technique for OFDM systems
2005
In this work a simple approach for the joint estimation-detection in a frequency selective severe fading environment of OFDM signals adopting PSK constellations is presented. A linear predictor of suitable order is adopted for the channel estimation in the frequency domain. The predictor coefficients are estimated on the basis of a sample estimation of the autocorrelation of the channel frequency response, aided by a preliminary differential decoding, in a blockwise manner. The detection technique proposed here is based on a simple tree search where a small number of best survivor paths are maintained at each step. Despite the simplicity of above detection approach, the simulation results s…
Weighted-average least squares estimation of generalized linear models
2018
The weighted-average least squares (WALS) approach, introduced by Magnus et al. (2010) in the context of Gaussian linear models, has been shown to enjoy important advantages over other strictly Bayesian and strictly frequentist model averaging estimators when accounting for problems of uncertainty in the choice of the regressors. In this paper we extend the WALS approach to deal with uncertainty about the specification of the linear predictor in the wider class of generalized linear models (GLMs). We study the large-sample properties of the WALS estimator for GLMs under a local misspecification framework that allows the development of asymptotic model averaging theory. We also investigate t…