SCKS toolbox: Blind deconvolution of hemodynamic response

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F10%3APR24892" target="_blank" >RIV/00216305:26220/10:PR24892 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
SCKS toolbox: Blind deconvolution of hemodynamic response
Original language description
This toolbox contains implementation of square-root Cubature Kalman Filter and square-root Rauch-Tang-Striebel smoother (SCKF-SCKS). These algorithms perform joint estimation of the states, input and parameters of stochastic continuous-discrete state-space models. The state equations must have a form of ordinary differential equations, where their discretization is performed through an efficient local-linearization scheme. Additionally, the parameter noise covariance is estimated dynamicaly via stochastic Robbins-Monro approximation method, and the measurement noise covariance is estimated online as well, using combination of varitional Bayesian (VB) approach with nonlinear filter/smoother. In particular, this method was designed to perform the nonlinear blind deconvolution of hemodynamic responses from fMRI data to estimate the underlying neuronal signal.
Czech name
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Czech description
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Project
<a href="/en/project/1M0572" target="_blank" >1M0572: Data, algorithms, decision making</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Internal product ID
SCKS
Technical parameters
Software může být spuštěn v programovém prostředí Matlab na standardních PC.
Economical parameters
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Owner IČO
00216305
Owner name
Ústav biomedicínského inženýrství

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