Making sense of parameter estimation and model simulation in bioprocesses
Sign Up to like & getrecommendations! Published in 2020 at "Biotechnology and Bioengineering"
DOI: 10.1002/bit.27294
Abstract: Most articles that report fitted parameters for kinetic models do not include meaningful statistical information. This study demonstrates the importance of reporting a complete statistical analysis and shows a methodology to perform it, using functionalities… read more here.
Keywords: sense parameter; estimation model; parameter estimation; model ... See more keywords
Personalising cardiovascular network models in pregnancy: A two-tiered parameter estimation approach.
Sign Up to like & getrecommendations! Published in 2019 at "International journal for numerical methods in biomedical engineering"
DOI: 10.1002/cnm.3267
Abstract: Uterine artery Doppler waveforms are often studied to determine whether a patient is at risk of developing pathologies such as pre-eclampsia. Many uterine waveform indices have been developed, which attempt to relate characteristics of the… read more here.
Keywords: parameter estimation; pre eclampsia; model; arterial stiffness ... See more keywords
Adaptive parameter estimation for a general dynamical system with unknown states
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Robust and Nonlinear Control"
DOI: 10.1002/rnc.4819
Abstract: This paper is concerned with the design of a state filter for a time‐delay state‐space system with unknown parameters from noisy observation information. The key is to investigate new identification algorithms for interactive state and… read more here.
Keywords: system; state; state filter; parameter estimation ... See more keywords
Recursive parameter estimation methods and convergence analysis for a special class of nonlinear systems
Sign Up to like & getrecommendations! Published in 2019 at "International Journal of Robust and Nonlinear Control"
DOI: 10.1002/rnc.4824
Abstract: This paper is concerned with the joint estimation of states and parameters of a special class of nonlinear systems, ie, bilinear systems. The key is to investigate new estimation methods for interactive state and parameter… read more here.
Keywords: special class; convergence; estimation; state ... See more keywords
Distributed Parameter Estimation for Univariate Generalized Gaussian Distribution over Sensor Networks
Sign Up to like & getrecommendations! Published in 2017 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-016-0345-0
Abstract: Generalized Gaussian distribution (GGD) is one of the most prominent and widely used parametric distributions to model the statistical properties of various phenomena. Parameter estimation for these distributions becomes a fundamental problem. However, most of… read more here.
Keywords: distributed parameter; estimation; generalized gaussian; parameter estimation ... See more keywords
Recursive Least Squares and Multi-innovation Stochastic Gradient Parameter Estimation Methods for Signal Modeling
Sign Up to like & getrecommendations! Published in 2017 at "Circuits, Systems, and Signal Processing"
DOI: 10.1007/s00034-016-0378-4
Abstract: The sine signals are widely used in signal processing, communication technology, system performance analysis and system identification. Many periodic signals can be transformed into the sum of different harmonic sine signals by using the Fourier… read more here.
Keywords: parameter estimation; estimation; stochastic gradient; innovation ... See more keywords
A Variational Approximations-DIC Rubric for Parameter Estimation and Mixture Model Selection Within a Family Setting
Sign Up to like & getrecommendations! Published in 2021 at "Journal of Classification"
DOI: 10.1007/s00357-019-09351-3
Abstract: Mixture model-based clustering has become an increasingly popular data analysis technique since its introduction over fifty years ago, and is now commonly utilized within a family setting. Families of mixture models arise when the component… read more here.
Keywords: parameter estimation; family; model; model selection ... See more keywords
Cost function based on hidden Markov models for parameter estimation of chaotic systems
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DOI: 10.1007/s00500-018-3129-6
Abstract: In this note, we deal with parameter estimation methods of chaotic systems. The parameter estimation of the chaotic systems has some significant issues due to their butterfly effects. It can be formulated as an optimization… read more here.
Keywords: chaotic systems; parameter estimation; cost function;
Diffusion Process with Evolution and its Parameter Estimation
Sign Up to like & getrecommendations! Published in 2020 at "Cybernetics and Systems Analysis"
DOI: 10.1007/s10559-020-00293-y
Abstract: A discrete Markov process in an asymptotic diffusion environment with a uniformly ergodic embedded Markov chain can be approximated by an Ornstein–Uhlenbeck process with evolution. The drift parameter estimation is obtained using the stationarity of… read more here.
Keywords: parameter estimation; process evolution; process; diffusion ... See more keywords
Multiple thresholds in extremal parameter estimation
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DOI: 10.1007/s10687-018-0337-5
Abstract: Selecting the number of upper order statistics to use in extremal inference or selecting the threshold above which we perform the extremal inference is a common step in applications of extreme value theory. Not only… read more here.
Keywords: parameter estimation; multiple thresholds; thresholds extremal; extremal parameter ... See more keywords
Accurate parameter estimation for Bayesian network classifiers using hierarchical Dirichlet processes
Sign Up to like & getrecommendations! Published in 2018 at "Machine Learning"
DOI: 10.1007/s10994-018-5718-0
Abstract: This paper introduces a novel parameter estimation method for the probability tables of Bayesian network classifiers (BNCs), using hierarchical Dirichlet processes (HDPs). The main result of this paper is to show that improved parameter estimation… read more here.
Keywords: hierarchical dirichlet; estimation; bayesian network; parameter estimation ... See more keywords