We consider convex optimization problems in the presence of stochastic uncertainty. The
min-max sample-based solution is the solution obtained by minimizing the max of the cost …

The scenario approach is a recently introduced method to obtain feasible solutions to
chance-constrained optimization problems based on random sampling. It has been noted …

We consider optimization problems with nonconvex magnitude constraints on frequency or
angular responses encountered in many signal processing problems. To provide a solution …

This paper presents a novel multichannel audio equalization technique based on
evolutionary computation algorithms for tuning the filters coefficients. Specifically, two …

Hybrid filter bank (HFB) analog-to-digital systems permit wideband, high frequency
conversion. This paper presents mixed norm optimal design of digital synthesis filters of a …

In previous contributions, Calafiore and Campi (2006) and Campi et al.(2009b), it has been
shown that the scenario approach is a handy methodology to design control systems having …

Digital subscriber lines (DSL) are one of the major current broadband access technologies,
with a penetration of over 300 million DSL subscribers world-wide. Besides an increasing …

Based on recent results on randomized min-max convex problems, we present a technique
for building probability boxes that envelop the probability distribution of the costs incurred by …

In this work we provide new theoretical results fit for use by decision-makers called to cope
with uncertainty. We will focus on single-objective decision problems where a cost function …

Underwater acoustic channel is assumed to be one of the most challenging communication
channels because of its variable multipath effect. To reduce the receiver complexity, we …