Search results for "Autoregressive model"
showing 10 items of 120 documents
Reproduction of kinematics of cars involved in crash events using nonlinear autoregressive models
2012
Vehicle crashworthiness can be assessed by the variety of methods - the most common and direct one is a vehicle crash test. Visual inspection and obtained measurements, such as car acceleration, are used to examine impact severity of an occupant and overall car safety. However, those experiments are complex, time-consuming, and expensive. We propose a method to reproduce car kinematics during a collision using a feedforward neural network to estimate the system by use of nonlinear autoregressive (NAR) models. Specifically, feasibility of applying neural networks with an NAR model to the analysis of experimental data is explored by application to measurements of a vehicle crash test. This mo…
The effectiveness of the autoregressive models in forecasting the agricultural prices in Poland
2010
The forecast of agricultural prices is one of the most important factors in making decision on production farms. The appropriate forecast allows for limiting the risk connected with one’s economic activity. In this study autoregressive models have been used, which helped to determine the price forecast for agricultural products in the purchasing centers in the second half of 2010. To determine the quality of forecast the average ex-post errors of the past forecasts have been used. The achieved results show that autoregressive models are an effective tool in forecasting the agricultural prices in Poland.
Information Transfer in Linear Multivariate Processes Assessed through Penalized Regression Techniques: Validation and Application to Physiological N…
2020
The framework of information dynamics allows the dissection of the information processed in a network of multiple interacting dynamical systems into meaningful elements of computation that quantify the information generated in a target system, stored in it, transferred to it from one or more source systems, and modified in a synergistic or redundant way. The concepts of information transfer and modification have been recently formulated in the context of linear parametric modeling of vector stochastic processes, linking them to the notion of Granger causality and providing efficient tools for their computation based on the state&ndash
EEG-based biometrics: effects of template ageing
2020
This chapter discusses the effects of template ageing in EEG-based biometrics. The chapter also serves as an introduction to general biometrics and its main tasks: Identification and verification. To do so, we investigate different characterisations of EEG signals and examine the difference of performance in subject identification between single session and cross-session identification experiments. In order to do this, EEG signals are characterised with common state-of-the-art features, i.e. Mel Frequency Cepstral Coefficients (MFCC), Autoregression Coefficients, and Power Spectral Density-derived features. The samples were later classified using various classifiers, including Support Vecto…
Noninvasive assessment of baroreflex sensitivity in post-MI patients by an open loop parametric model of RR-systolic pressure interactions
2003
Noninvasive evaluation of baroreflex sensitivity is considered an important goal for diagnosis and prognosis in post-MI patients. Methodological approach and physiological measure conditions may be the main causes for the differences found with respect to the standard Phenylephrine test. In this study, three linear parametric models, describing variability and mutual interactions of RR interval and systolic arterial pressure (SAP), were compared in relation to their ability to quantify baroreflex gain, using the Phenylephrine test index (Phe/sub BRS/) as reference. By monovariate autoregressive (AR) model, bivariate AR model and open loop ARXAR model, specific gain indexes (/spl alpha//sub …
A Multi-Variate Predictability Framework to Assess Invasive Cardiac Activity and Interactions during Atrial Fibrillation
2017
Objective: This study introduces a predictability framework based on the concept of Granger causality (GC), in order to analyze the activity and interactions between different intracardiac sites during atrial fibrillation (AF). Methods: GC-based interactions were studied using a three-electrode analysis scheme with multi-variate autoregressive models of the involved preprocessed intracardiac signals. The method was evaluated in different scenarios covering simulations of complex atrial activity as well as endocardial signals acquired from patients. Results: The results illustrate the ability of the method to determine atrial rhythm complexity and to track and map propagation during AF. Conc…
Causal linear parametric model for baroreflex gain assessment in patients with recent myocardial infarction
2001
Spectral and cross-spectral analysis of R-R interval and systolic arterial pressure (SAP) spontaneous fluctuations have been proposed for noninvasive evaluation of baroreflex sensitivity (BRS). However, results are not in good agreement with clinical measurements. In this study, a bivariate parametric autoregressive model with exogenous input (ARXAR model), able to divide the R-R variability into SAP-related and -unrelated parts, was used to quantify the gain (αARXAR) of the baroreflex regulatory mechanism. For performance assessing, two traditional noninvasive methods based on frequency domain analysis [spectral, baroreflex gain by autogressive model (αAR); cross-spectral, baroreflex gain…
Spectral decomposition of RR-variability obtained by an open loop parametric model for the diagnosis of neuromediate syncope
2002
The role of the cardiovascular regulatory mechanism in patients with neuromediate syncope (NS) is poorly understood. The aim of this study was to accomplish continuous non-invasive analysis of the baroreflex mechanism in patients during a head-tip tilt-table test (HTT) using an open-loop autoregressive model with exogenous input. The model describes the causal dependence of the RR interval on the systolic arterial pressure (SAP) variability. Thus, RR variability results as the linear composition of SAP-dependent (Pdep) and SAP-independent parts of the RR power (P). Further, the model allows the estimation of the baroreflex gain using the modulus of the transfer function (G) from SAP to RR i…
Introducing the DYNAMICS framework of moment-to-moment development in achievement motivation
2022
This article introduces a new theoretical and psychometric framework describing moment-to-moment development and inter-dependencies of achievement motivation in terms of the situated expectancy-value theory, by introducing dynamical systems concepts into this line of research. As a first empirical example of a study using this framework, we examined whether task values, costs, and success expectancies measured in a learning situation (time point t) predicted themselves and each other at the next situation (t + 1; 27 min later) within a weekly university lecture. Situational task values, expectancies, and costs were assessed using the experience sampling method in 155 university teacher trai…
Assessing Transfer Entropy in cardiovascular and respiratory time series: A VARFI approach
2021
In the study of complex biomedical systems represented by multivariate stochastic processes, such as the cardiovascular and respiratory systems, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. Recently, the quantification of multiscale complexity based on linear parametric models, incorporating autoregressive coefficients and fractional integration, encompassing short term dynamics and long-range correlations, was extended to multivariate time series. Within this Vector AutoRegressive Fractionally Integrated (VARFI) framework formalized for Gaussian processes, in this work we propose to estimate the Transfer Entropy, or equivalently G…