LYSIS (the Greek word for “solution”) is an interactive software of a set of modular programs (each performing a specific task) that provide an integrated computing environment for data analysis and system modeling. Unique capabilities of LYSIS include input-output nonlinear system modeling and the novel methodology of “Principal Dynamic Modes” (PDMs). This package has evolved over time to incorporate emerging methodologies developed by the Biomedical Simulations Resource (BMSR) at USC, under the supervision of Prof. V.Z. Marmarelis.
LYSIS 7.2 – Matlab version is the current version and is focused on the unique capabilities of input-output nonlinear system modeling using the Volterra-Wiener approach and its efficient variants that have been developed and tested by the BMSR over the years, utilizing Laguerre expansions of the kernels and the novel concept/tool of Principal Dynamic Modes (PDMs). The source code of modular Matlab programs are made available that can be incorporated in the Matlab computational environment of the user.
Early versions are also available for UNIX environments, distributed as source code that can be compiled for each UNIX implementation (e.g., Solaris, HPUX, Linux) Email us for the Source Code!!
The development of LYSIS is supported by the Biomedical Simulations Resource (BMSR) in the Department of Biomedical Engineering at the University of Southern California, under support from the National Institute for Biomedical Imaging and Bioengineering (P41-EB001978) and the National Center for Research Resources (P41-RR01861) of the National Institutes of Health. LYSIS is made available to the biomedical community at large free of charge in order to promote research in this area and enhance the computational capabilities of biomedical investigators nationwide. The BMSR holds the copyright of LYSIS and its use must be acknowledged by individual investigators in their research publications.
- Operating System
- Windows XP/Vista/7
- Sun/Unix: Solaris 2.x
Key relevant publications
Marmarelis, V.Z. Identification of nonlinear biological systems using Laguerre expansions of kernels. Annals of Biomedical Engineering 21:573-589, 1993.[PDF]
Marmarelis, V.Z. Modeling methodology for nonlinear physiological systems. Annals of Biomedical Engineering 25:239-251, 1997. [PDF]
Marmarelis, V.Z. & X. Zhao. Volterra models and three-layer perceptrons. IEEE Transactions on Neural Networks 8(6):1421-1433, 1997. [PDF]
Marmarelis, V.Z. Nonlinear Dynamic Modeling of Physiological Systems. IEEE Press & Wiley Interscience, New Jersey, 2004.
Marmarelis, V.Z. Nonlinear Dynamic Modeling of Physiological Systems, Wiley Interscience & IEEE Press, New Jersey, 2004.
Marmarelis V.Z., D.C. Shin, D. Song, R.E. Hampson, S.A. Deadwyler, and T.W. Berger. Nonlinear modeling of dynamic interactions within neuronal ensembles using Principal Dynamic Modes. Journal of Computational Neuroscience (in press). DOI 10.1007/s10827-012-0407-7
Marmarelis V.Z., D.C. Shin, M.E. Orme, and R. Zhang. Closed-loop dynamic modeling of cerebral hemodynamics. Annals of Biomedical Engineering (in press). DOI: 10.1007/s10439-012-0736-8
Unique Features of LYSIS
Specific features of LYSIS that cannot be found in commercially available packages include the efficient kernel estimation using Laguerre expansions and the use of Principal Dynamic Modes (PDMs). These enable input-output modeling of dynamic nonlinear systems with relatively short data-records (even in the presence of considerable noise).