Search results for "linear prediction"
showing 10 items of 18 documents
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…
A note on adjusted responses, fitted values and residuals in Generalized Linear Models
2014
Adjusted responses, adjusted fitted values and adjusted residuals are known to play in Generalized Linear Models the role played in Linear Models by observations, fitted values and ordinary residuals. We think this parallelism, which was widely recognized and used in the early literature on Generalized Linear Models, has been somewhat overlooked in more recent presentations. We revise this parallelism, systematizing and proving some results that are either scattered or not satisfactorily spelled out in the literature. In particular, we formally derive the asymptotic dispersion matrix of the (scaled) adjusted residuals, by proving that in Generalized Linear Models the fitted values are asym…
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) …
On the use of generalized harmonic means in image processing using multiresolution algorithms
2019
In this paper we design a family of cell-average nonlinear prediction operators that make use of the generalized harmonic means and we apply the resulting schemes to image processing. The new famil...
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…
Fitting generalized linear models with unspecified link function: A P-spline approach
2008
Generalized linear models (GLMs) outline a wide class of regression models where the effect of the explanatory variables on the mean of the response variable is modelled throughout the link function. The choice of the link function is typically overlooked in applications and the canonical link is commonly used. The estimation of GLMs with unspecified link function is discussed, where the linearity assumption between the link and the linear predictor is relaxed and the unspecified relationship is modelled flexibly by means of P-splines. An estimating algorithm is presented, alternating estimation of two working GLMs up to convergence. The method is applied to the analysis of quit behavior of…
Pairwise and higher-order measures of brain-heart interactions in children with temporal lobe epilepsy
2022
Abstract Objective. While it is well-known that epilepsy has a clear impact on the activity of both the central nervous system (CNS) and the autonomic nervous system (ANS), its role on the complex interplay between CNS and ANS has not been fully elucidated yet. In this work, pairwise and higher-order predictability measures based on the concepts of Granger Causality (GC) and partial information decomposition (PID) were applied on time series of electroencephalographic (EEG) brain wave amplitude and heart rate variability (HRV) in order to investigate directed brain-heart interactions associated with the occurrence of focal epilepsy. Approach. HRV and the envelopes of δ and α EEG activity re…
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…
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…
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…