Matrix-based analytical methods for recasting Jacobian models to power-law models

Michael A. Idowu, James L. Bown

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


New methods for inferring data-consistent, selfreconfigurable power-law models from time series data are required and developed. These novel methods may be categorised into two broad groups, namely: straightforward (or direct) inference methods based on power-law models; and a jacobian based indirect inference method. The direct method involves applying direct means to infer a power-law model from time series data. The indirect method, however, uses a new system identification method to first infer a jacobian model as instant and temporal solution to the inverse problem before recasting the inferred jacobian model to corresponding power-law model using our newly developed recast technique. The recast method, in addition to normal behaviour, also provides a novel analytical technique for integrating power-law and jacobian models together. The modelling approach we have developed extends previous work on matrix-based network inference to model interoperability and multiple model transformation in terms of finding two distinct models (solutions) to an inverse problem.
Original languageEnglish
Title of host publicationProceedings of the eighth EUROSIM Congress on Modelling and Simulation, EUROSIM 2013, September 10-13, Cardiff, Wales
EditorsKhalid Al-Begain, David Al-Dabass, Alessandra Orsoni, Richard Cant, Richard Zobel
Place of PublicationLos Alamitos, CA
PublisherIEEE Computer Society
Number of pages9
ISBN (Print)970769550732
Publication statusPublished - 2013
Event8th EUROSIM Congress on Modelling and Simulation - Wales Millennium Centre, Cardiff, United Kingdom
Duration: 10 Sep 201313 Sep 2013
Conference number: 8th


Other8th EUROSIM Congress on Modelling and Simulation
Abbreviated titleEUROSIM 2013
CountryUnited Kingdom
Internet address

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