We propose a method for deriving computationally efficient representations of periodic solutions of parameterized systems of nonlinear ordinary differential equations. These representations depend on parameters of the system explicitly, as quadratures of parameterized computable functions. The method applies to systems featuring both linear and nonlinear parametrization, and time-varying right-hand-side; it opens possibilities to invoke scalable parallel computations for numerical evaluation of solutions for various parameter values. Application of the method to parameter estimation problems is illustrated with constructing an algorithm for state and parameter estimation for the Morris-Lecar system
A technique for obtaining approximate periodic solutions to nonlinear ordinary differential equation...
This dissertation expands on existing work to develop a dynamical state and parameter estimation met...
Often in mathematical modeling, it is necessary to estimate numerical values for parameters occurrin...
We propose a method for deriving computationally efficient representations of periodic solutions of ...
Developing mathematical models involves joining theory and experimental or observational data. The m...
We propose a novel method for fast and scalable evaluation of periodic solutions of systems of ordin...
In this book, we study theoretical and practical aspects of computing methods for mathematical model...
This paper introduces a systematic approach to synthesize linear parameter-varying (LPV) representat...
AbstractSystems of autonomous first-order ordinary differential equations are considered (dimension ...
This report treats a new approach to the problem of periodic signal estimation. The idea is to model...
Subsampling of a linear periodically time-varying system results in a collection of linear time-inva...
In computational science it is common to describe dynamic systems by mathematical models in forms of...
In this paper, we propose an algorithm for state and parameter estimation of nonlinear dynamical sys...
Typescript (photocopy).New results in the theory and application of linear periodic differential equ...
We present an efficient method for estimating variables and parameters of a given system of ordinary...
A technique for obtaining approximate periodic solutions to nonlinear ordinary differential equation...
This dissertation expands on existing work to develop a dynamical state and parameter estimation met...
Often in mathematical modeling, it is necessary to estimate numerical values for parameters occurrin...
We propose a method for deriving computationally efficient representations of periodic solutions of ...
Developing mathematical models involves joining theory and experimental or observational data. The m...
We propose a novel method for fast and scalable evaluation of periodic solutions of systems of ordin...
In this book, we study theoretical and practical aspects of computing methods for mathematical model...
This paper introduces a systematic approach to synthesize linear parameter-varying (LPV) representat...
AbstractSystems of autonomous first-order ordinary differential equations are considered (dimension ...
This report treats a new approach to the problem of periodic signal estimation. The idea is to model...
Subsampling of a linear periodically time-varying system results in a collection of linear time-inva...
In computational science it is common to describe dynamic systems by mathematical models in forms of...
In this paper, we propose an algorithm for state and parameter estimation of nonlinear dynamical sys...
Typescript (photocopy).New results in the theory and application of linear periodic differential equ...
We present an efficient method for estimating variables and parameters of a given system of ordinary...
A technique for obtaining approximate periodic solutions to nonlinear ordinary differential equation...
This dissertation expands on existing work to develop a dynamical state and parameter estimation met...
Often in mathematical modeling, it is necessary to estimate numerical values for parameters occurrin...