Linear functions are used to model a broad range of real-world problems. The ability to solve linear equations and inequalities is an essential skill for analysing these models. This section covers ...

This code is designed to solve Bayesian quantile regression model with linear inequality constraints. Leveraging asymmetric Laplace distributions, we propose two novel Gibbs sampling methods based on ...

Abstract: This paper discusses an approach to robust control law design for fault-tolerant systems. Based on the assumption that the effects of faults can be expressed in ...

An algorithm for computing parametric linear quantile regression estimates subject to linear inequality constraints is described. The algorithm is a variant of the interior point algorithm described ...

ABSTRACT: This paper considers the problem of robust non-fragile control for a class of two-dimensional (2-D) discrete uncertain systems described by the Fornasini-Marchesini second local state-space ...

Abstract: In this paper, some new non-linear integral inequalities are established. These inequalities can be used in the study of stability problems of perturbed dynamic systems. As applications, ...

E6602 is typically taught once per year in the Spring semester. The information below is meant to provide a snapshot of the material covered. Students will learn to recognize, model, formulate and ...

\({\textless}\) \({y}~{\textless}~{x}\) reads as ‘\({x}\) is greater than \({y}\)’ or ‘\({y}\) is less than \({x}\)’ \({\textgreater}\) \({7}~{\textgreater ...

Often in real life we find ourselves in situations that can be represented mathematically by inequalities. For example, if we want to take a taxi, we may find that the charge is £1.50 standard charge ...