Network-based Observability and Controllability Analysis of Dynamical Systems: the NOCAD toolbox. 2019

Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
Department of Computer Science and Systems Technology, University of Pannonia, Egyetem u. 10, Veszprém, 8200, Hungary.

The network science-based determination of driver nodes and sensor placement has become increasingly popular in the field of dynamical systems over the last decade. In this paper, the applicability of the methodology in the field of life sciences is introduced through the analysis of the neural network of Caenorhabditis elegans. Simultaneously, an Octave and MATLAB-compatible NOCAD toolbox is proposed that provides a set of methods to automatically generate the relevant structural controllability and observability associated measures for linear or linearised systems and compare the different sensor placement methods.

UI MeSH Term Description Entries
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D000818 Animals Unicellular or multicellular, heterotrophic organisms, that have sensation and the power of voluntary movement. Under the older five kingdom paradigm, Animalia was one of the kingdoms. Under the modern three domain model, Animalia represents one of the many groups in the domain EUKARYOTA. Animal,Metazoa,Animalia
D016571 Neural Networks, Computer A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming. Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D017173 Caenorhabditis elegans A species of nematode that is widely used in biological, biochemical, and genetic studies. Caenorhabditis elegan,elegan, Caenorhabditis

Related Publications

Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
December 2011, IEEE transactions on neural networks,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
February 2018, Scientific reports,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
February 2017, Chaos (Woodbury, N.Y.),
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
August 2018, Physical review. E,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
June 1964, Proceedings of the National Academy of Sciences of the United States of America,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
January 2018, PloS one,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
January 2014, TheScientificWorldJournal,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
March 1977, Computer programs in biomedicine,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
September 1976, Journal of theoretical biology,
Dániel Leitold, and Ágnes Vathy-Fogarassy, and János Abonyi
February 2013, Bioinformatics (Oxford, England),
Copied contents to your clipboard!