In this paper we discuss an inclusion method for solving rectangular (over- and under-determined) dense linear systems where the input data are uncertain and vary within ...

These are just a few of the many interesting and important problems that were previously excluded from the teaching curriculum as being too difficult but that can now be ...

The Laplace equation for an ellipse is solved by the method of separation of variables. The resulting one-dimensional differential equations are solved with Mathieu ...

This paper introduces a novel approach for designing an analog circuit under simultaneous consideration of DC and AC design specifications. Such specifications are restricted ...

In this tutorial type paper a Mathematica function for Support Vector Regression has been developed. Summarizing the main definitions and theorems of SVR, the detailed ...

Mathematica provides the functions Constrained Max and Constrained Min to solve linear programming problems. These functions do not handle problems that require that some ...

The development version of Mathematica contains extensive support for piecewise functions throughout the system. An arbitrary piecewise function (with a finite number of ...

Maxwell's equations in differential form are mapped onto two dimensions and discretized. Mathematica is used to solve the discretized equations for a fine mesh, with each ...

The objective of global optimization (GO) is to find the best solution of nonlinear decision models that often have a multitude of global and local optima. GO is of great ...

The chasing method proposed by Gelfand and Lokutzievskii and implemented in the Mathematica package "Numerical Solution of Linear Boundary Value Problems" is described. This ...