Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Ladislav Jirsa"'
Publikováno v:
Informatics in Medicine Unlocked, Vol 7, Iss , Pp 23-33 (2017)
The Bayesian identification of a linear regression model (called the biphasic model) for time dependence of thyroid gland activity in 131I radioiodine therapy is presented. Prior knowledge is elicited via hard parameter constraints and via the mergin
Externí odkaz:
https://doaj.org/article/8f8738e0fe6c4a56adbdd7dcfbe7a761
Publikováno v:
Informatics in Control, Automation and Robotics ISBN: 9783030631925
We investigate sensor network nodes that sequentially infer states with bounded values, and affected by noise that is also bounded. The transfer of knowledge between such nodes is the principal focus of this chapter. A fully Bayesian framework is ado
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8f1b5aeda9026ff503c44b80e246ce21
https://doi.org/10.1007/978-3-030-63193-2_9
https://doi.org/10.1007/978-3-030-63193-2_9
Publikováno v:
Knowledge-Based Systems. 238:107879
This paper considers the problem of Bayesian transfer learning-based knowledge fusion between linear state-space processes driven by uniform state and observation noise processes. The target task conditions on probabilistic state predictor(s) supplie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7c6e94c31b239f85989f15bbafdf811a
https://doi.org/10.1016/j.knosys.2021.107879
https://doi.org/10.1016/j.knosys.2021.107879
Autor:
Ladislav Jirsa, Lenka Pavelková
Publikováno v:
International Journal of Adaptive Control and Signal Processing. 31:1184-1192
Summary This paper proposes a recursive algorithm for the estimation of a stochastic autoregressive model with an external input. The noise of the involved model is described by a uniform distribution. The model parameters are estimated using the Bay
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::68d37c464d12eacb952fa9b812fd9b51
https://doi.org/10.1002/acs.2756
https://doi.org/10.1002/acs.2756
Publikováno v:
Informatics in Control, Automation and Robotics ISBN: 9783030319922
ICINCO (Selected Papers)
ICINCO (Selected Papers)
This paper proposes a one-step-ahead Bayesian output predictor for the linear stochastic state space model with uniformly distributed state and output noises. A model with discrete-time inputs, outputs and states is considered. The model matrices and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efa49c1039c5b7c8c71cb669ddb0069f
https://doi.org/10.1007/978-3-030-31993-9_27
https://doi.org/10.1007/978-3-030-31993-9_27
Publikováno v:
Informatics in Medicine Unlocked, Vol 7, Iss, Pp 23-33 (2017)
The Bayesian identification of a linear regression model (called the biphasic model) for time dependence of thyroid gland activity in 131I radioiodine therapy is presented. Prior knowledge is elicited via hard parameter constraints and via the mergin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f5104741e53b8b85db4e3b6df869aa10
http://www.sciencedirect.com/science/article/pii/S2352914816300338
http://www.sciencedirect.com/science/article/pii/S2352914816300338
Publikováno v:
ICINCO (1)
The paper presents an optimal Bayesian transfer learning technique applied to a pair of linear state-space processes driven by uniform state and observation noise processes. Contrary to conventional geometric approaches to boundedness in filtering pr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c8a1d4b923cc52b62c346deb4d6b5d2
https://doi.org/10.5220/0007854104990506
https://doi.org/10.5220/0007854104990506
Autor:
Lenka Pavelková, Ladislav Jirsa
Publikováno v:
ICINCO (1)
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::01734c39d0f0d8d33bd084401db58959
https://doi.org/10.5220/0006933803880394
https://doi.org/10.5220/0006933803880394
Publikováno v:
International Journal of Adaptive Control and Signal Processing. 17:133-148
Real-world, multidimensional, dynamic, non-linear processes typically exhibit many distinct modes of operation. Mixtures of dynamic models improve greatly on traditional one-component linear models in this context. Improved prediction then points the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d6e61c019dfe84bd5c4c30df3455a72
https://doi.org/10.1002/acs.743
https://doi.org/10.1002/acs.743
Autor:
Lenka Pavelková, Ladislav Jirsa
Publikováno v:
ICINCO (1)
A modular framework for monitoring complex systems contains blocks that evaluate condition of single signals, typically of sensors. The signals are modelled and their values must be found within the prescribed bounds. However, an abrupt change of the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f1a2044d30f3a8046516a5570016a34e
https://doi.org/10.5220/0005545706030607
https://doi.org/10.5220/0005545706030607