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Rhythmic, periodic processes are ubiquitous in biological systems; for example, the heart beat, walking, circadian rhythms and the menstrual cycle. Modeling these processes with high delity as peri...
This paper presents work on parameter estimation methods for bursting neural models. In our approach we use both geometrical features specific to bursting, as well as general features such as perio...
We demonstrate the generalizability of the Extended Baum-Welch (EBW) algorithm not only for HMM parameter estimation but for decoding as well. We show that there can exist a general function associate...
The objective of this study was to estimate genetic parameters that are to be used for across-herd genetic evaluations of seed stock pigs at GGP level. Performance data with pedigree information colle...
We investigate the FFT (Fast Fourier Transform) model and G-CSF (granulocytecolony-stimulating factor) treatment of CN (Cyclical Neutropenia). We collect grey collies and normal dog!ˉs data from CN an...
Abstract: This work propose a sequential procedure which is useful to select the best model among several nested non-linear models and to estimate efficiently the parameters of the chosen model. At ea...
Approximating joint smoothing distributions using particle-based methods is a well-known issue in statistical inference when operating on general state space hidden Markov models (HMM). In this paper ...
We explore the precision with which the Einstein Telescope (ET) will be able to measure the parameters of intermediate–massratio inspirals (IMRIs), i.e., the inspirals of stellar mass compact object...
We explore the precision with which the Einstein Telescope (ET) will be able to measure the parameters of intermediate–massratio inspirals (IMRIs), i.e., the inspirals of stellar mass compact object...
We study multipath parameter estimation from orthogonal frequency division multiplex signals transmitted over doubly dispersive mobile radio channels. We are interested in cases where the transmissio...
The paper considers gossip distributed estimation of a (static) distributed random field (a.k.a., large scale unknown parameter vector) observed by sparsely interconnected sensors, each of which only ...
The subject of this paper is an investigation of the nonlinear contributions to the spectrum of the integrated Sachs-Wolfe (iSW) effect. We derive the corrections to the iSW-auto spectrum and the iSW-...
Coupled hydrogeophysical methods infer hydrological and petrophysical parameters directly from geophysical measurements. Widespread methods do not explicitly recognize uncertainty in parameter estimat...
The accuracy of parameter estimation is critical when digitally modeling a ship. A parameter estimation method with constraints was developed, based on the variational method. Performance functions an...
This study provides results for the optimization strategy of highly parameterized models, especially with a high number of unknown input parameters and joint problems in terms of sufficient parameter ...

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