Information-based complexity
The computational complexity of differential and integral equations: an information-based approach
The computational complexity of differential and integral equations: an information-based approach
Complexity and real computation
Complexity and real computation
When are quasi-Monte Carlo algorithms efficient for high dimensional integrals?
Journal of Complexity
Complexity and information
| Hi-index | 0.00 |
Many of the mathematical models used in fields such as the physical sciences, engineering, economics, and mathematical finance use continuous mathematical models. These models typically require the numerical solution of multivariate problems (often in a very large number of variables) such as integrals, ordinary and partial differential equations (q.v.), optimization, approximation, integral equations, and nonlinear equations. The study of the computational complexity of continuous mathematical problems is called information-based complexity (IBC). This is a branch of computational complexity (q.v.) which studies the minimal computer resources (typically time or space) needed to solve mathematically posed problems.