We consider the problem of identification of linear systems in the presence of measurement noise which is unknown but bounded in magnitude by some 6 > 0. We focus on the case of linear systems with a finite impulse response. It is known that the optimal identification error is related (within a factor of 2) to the diameter of a so-called uncertainty set and… (More)
We study the maturation of the antibody population following primary antigen presentation as a global optimization problem. Emphasis is placed on the trade-off between the safety of mutations that lead to local improvements to the antibody's affinity and the necessity of eventual mutations that result in global reconfigurations in the antibody's shape. The… (More)
For a class of stochastic restart algorithms we address the effect of a nonzero level of randomization in maximizing the convergence rate for general energy landscapes. The resulting characterization of the optimal level of randomization is investigated computationally for random as well as para-metric families of rugged energy landscapes.