Search results for "least square"

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

Search strategies in innovation networks: The case of the Hungarian food industry

2020

In the food sector, open innovation has become of particular interest. This paper considers open innovation search strategies in the food and beverages industry and examines the probability of using different innovation sources with respect to the type of innovation. Although the information search for new ideas, tools and solutions in the innovation process regarding the scope and depth is well explored and interpreted in the literature, the probability of using the different sources with respect to type of innovation is rarely investigated. To answer these questions, first a probit, then OLS regression model is adopted, in order to understand the chance of a specific source of information…

Analysis of Caffeine, Sweeteners, and Other Additives in Beverages by Vibrational Spectroscopy

2001

This chapter presents a review of the scientific literature on the use of vibrational spectroscopy, near-infrared (NIR), mid-infrared (mid-IR), and Raman, for the analysis of caffeine, sweeteners, and other additives in beverages and related products. Direct analysis procedures of coffee and tea, for both classification according to precedence or variety and quantitative determination of caffeine, are available. For beverage analysis, caffeine has been determined by direct attenuated total reflection (ATR) measurement or by transmission spectroscopy in the mid-IR region after extraction with chloroform. Different strategies have been employed for the analysis of sweeteners in beverages and …

Investigating the Heartbeat-evoked cortical responses through parametric Time-Varying Information Measures

2022

Recent studies showed that the information coming from the heart is constantly processed by the brain. One index to study this process is the heartbeat-evoked potential (HEP), represented by an event-related potential component related to the cortical processing of the heartbeat. In this study we propose an approach to investigate the heartbeat-evoked EEG responses, based on quantifying the changes induced by the heartbeat on the predictability of the brain dynamics. The regularity of EEG signals is assessed through the Information Storage (IS) computed with a time-varying approach able to derive the temporal profile of the measure for each time point. Results show a modulation in the regul…

Impact of the terrestrial reference frame on the determination of the celestial reference frame.

2022

Currently three up-to-date Terrestrial Reference Frames (TRF) are available, the ITRF2014 from IGN, the DTRF2014 from DGFI-TUM, and JTRF2014 from JPL. All use the identical input data of space-geodetic station positions and Earth orientation parameters, but the concept of combining these data is fundamentally different. The IGN approach is based on the combination of technique solutions, while the DGFI is combining the normal equation systems. Both yield in reference epoch coordinates and velocities for a global set of stations. JPL uses a Kalman filter approach, realizing a TRF through weekly time series of geocentric coordinates. As the determination of the CRF is not independent of the T…

System identification via optimised wavelet-based neural networks

2003

Nonlinear system identification by means of wavelet-based neural networks (WBNNs) is presented. An iterative method is proposed, based on a way of combining genetic algorithms (GAs) and least-square techniques with the aim of avoiding redundancy in the representation of the function. GAs are used for optimal selection of the structure of the WBNN and the parameters of the transfer function of its neurones. Least-square techniques are used to update the weights of the net. The basic criterion of the method is the addition of a new neurone, at a generic step, to the already constructed WBNN so that no modification to the parameters of its neurones is required. Simulation experiments and compa…

LASSO regression via smooth L1-norm approximation

2010

This paper discusses estimation of regression model with LASSO penalty when the L1-norm is replaced with its parametric smooth approximation. The resulting parameter estimators are more manageable than those from standard LASSO, standard errors are easy computed via a sandwich formula, and the model degrees of freedom may be computed straightforwardly. Moreover the resulting objective function may be minimized using usual optimization algorithms for regular models, for instance Newton-Raphson or iterative least squares.

OUTLIER RECOGNITION AND ROBUST WEIGHTING PROCEDURES APPLIED IN CATION ORDERING-DISORDERING KINETIC DATA PROCESSING

2011

Updating strategies for distance based classification model with recursive least squares

2022

Abstract. The idea is to create a self-learning Minimal Learning Machine (MLM) model that is computationally efficient, easy to implement and performs with high accuracy. The study has two hypotheses. Experiment A examines the possibilities of introducing new classes with Recursive Least Squares (RLS) updates for the pre-trained self learning-MLM model. The idea of experiment B is to simulate the push broom spectral imagers working principles, update and test the model based on a stream of pixel spectrum lines on a continuous scanning process. Experiment B aims to train the model with a significantly small amount of labelled reference points and update it continuously with (RLS) to reach ma…

Fusion of the 1H NMR data of serum, urine and exhaled breath condensate in order to discriminate chronic obstructive pulmonary disease and obstructiv…

2015

Chronic obstructive pulmonary disease, COPD, affects the condition of the entire human organism and causes multiple comorbidities. Pathological lung changes lead to quantitative changes in the composition of the metabolites in different body fluids. The obstructive sleep apnea syndrome, OSAS, occurs in conjunction with chronic obstructive pulmonary disease in about 10–20 % of individuals who have COPD. Both conditions share the same comorbidities and this makes differentiating them difficult. The aim of this study was to investigate whether it is possible to diagnose a patient with either COPD or the OSA syndrome using a set of selected metabolites and to determine whether the metabolites t…