Parameter estimation in differential equation models is a critical endeavour in the mathematical modelling of dynamic systems. Such models, represented by ordinary differential equations (ODEs), ...

Model natural and engineered hydraulic and hydrologic systems. Manage large datasets and develop models for hydrodynamics. Gain in-depth modeling experience using real-world case studies in a ...

Stochastic differential equations have been shown useful in describing random continuous time processes. Biomedical experiments often imply repeated measurements on a series of experimental units and ...

Develop a foundation of analytical mechanics and multiphysics modeling. Use individual and team exercises to build skills for a dynamic systems approach. Engineered systems increasingly must exploit ...

This course covers differential equation derivation to model systems, solving these equations through Laplace transforms to determine transfer functions for simple mechanical, electrical, and ...

(Nanowerk News) Clemens Heitzinger, assistant professor of applied mathematics in the School of Mathematical and Statistical Sciences, has recently been awarded the prestigious START Prize by the ...

Differential equations are commonly used to model dynamical deterministic systems in applications. When statistical parameter estimation is required to calibrate theoretical models to data, classical ...

Cancer is viewed as a multistep process whereby a normal cell is transformed into a cancer cell through the acquisition of mutations. We reduce the complexities of cancer progression to a simple set ...

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...