Results 51 to 60 of about 2,190,995 (307)
Journal of Statistical Software, 2011 This paper uses several examples to show how the econometrics program RATS can be used to analyze state space models. It demonstrates Kalman filtering and smoothing, estimation of hyperparameters, unconditional and conditional simulation.
Thomas Doan
doaj
State-Space Methods for µ-Analysis
, 1994 This paper discusses state-space methods for analyzing stability of continuous time linear systems subject to structured uncertainties. Four types of uncertainties are discussed: linear parametric and dynamic uncertainties (real and complex µ) and nonlinear parametric and dynamic uncertainties.
Helmersson, Anders, A. Helmersson
openaire +2 more sources
A state-space method for language modeling [PDF]
2003 IEEE Workshop on Automatic Speech Recognition and Understanding (IEEE Cat. No.03EX721), 2004 A new state-space method for language modeling is presented. The complexity of the model is controlled by choosing the dimension of the state instead of the smoothing and back-off methods common in n-gram modeling. The model complexity also controls the generalization ability of the model, allowing the model to handle similar words in a similar manner.
V. Siivola, A. Honkela
openaire +1 more source
FEBS Letters, EarlyView.Septin 9 polybasic domains couple phosphoinositide‐rich membrane binding to centrosome positioning, Golgi organization, and microtubule acetylation to control epithelial polarity. Their loss disrupts this axis, causing centrosome mispositioning, Golgi fragmentation, reduced microtubule acetylation, and polarity inversion via upregulation of the ...
Ting ting Cai +4 more
wiley +1 more source
FEBS Letters, EarlyView.An unexpected alternative interaction site for ethyl viologen was identified in formate dehydrogenase 1 from Methylorubrum extorquens. Combined mutagenesis, kinetic analysis, and docking revealed that aromatic residues near an iron–sulfur cluster enable flavin mononucleotide‐independent electron transfer, offering a framework for engineering improved ...
Eleni G. Poloniataki, Yong Hwan Kim
wiley +1 more source
Recursive prediction error methods for online estimation in nonlinear state-space models [PDF]
Modeling, Identification and Control, 1994 Several recursive algorithms for online, combined state and parameter estimation in nonlinear state-space models are discussed in this paper. Well-known algorithms such as the extended Kalman filter and alternative formulations of the recursive ...
Dag Ljungquist, Jens G. Balchen
doaj +1 more source
FEBS Letters, EarlyView.The physical dimensions and shape of bacterial cells define the surface area available to acquire nutrients and the volume available for synthesizing proteins and DNA. Here, we use computational systems biology to decode the importance of cell geometry as a major determinant of prokaryotic phenotype, including growth rate and metabolic efficiency. This
Ross P. Carlson +6 more
wiley +1 more source
Forecasting of commodities prices using a multi-factor PDE model and Kalman filtering
IET Cyber-Physical Systems, 2018 This study proposes a method for forecasting commodities prices using Schwartz partial differential equation (PDE) and Kalman filtering. The method is applicable to both the single-factor and the multi-factor Schwartz PDE.
Gerasimos Rigatos +4 more
doaj +1 more source
Eletrônica de Potência, 2020 This paper presents a steady-state analysis and design methodology for the Class-E² resonant DC/DC converter. The converter is represented in a normalized state-space model that is independent of specifications and real system components, like as ...
Lucas S. Mendonça +3 more
doaj +1 more source
Spike-based reinforcement learning in continuous state and action space: when policy gradient methods fail. [PDF]
PLoS Computational Biology, 2009 Changes of synaptic connections between neurons are thought to be the physiological basis of learning. These changes can be gated by neuromodulators that encode the presence of reward.
Eleni Vasilaki +4 more
doaj +1 more source