Constrained Maximum Likelihood (CML) is a new software module developed at Aptech Systems for the generation of maximum likelihood estimates of statistical models with general constraints on parameters. These constraints can be linear or nonlinear, equality or inequality. The software uses the Sequential Quadratic Programming method with various descent algorithms to iterate from a given starti...

In the present paper, we would like to draw attention to a possible generalized Fisher information that ts well in the formalism of nonextensive thermostatistics. This generalized Fisher information is de ned for densities on R. Just as the maximum Rényi or Tsallis entropy subject to an elliptic moment constraint is a generalized qGaussian, we show that the minimization of the generalized Fishe...

A Radau pseudospectral method is derived for solving state-inequality path constrained optimal control problems. The continuous-time state-inequality path constrained optimal control problem is modified by applying a set of tangency conditions at the entrance of the activity of the path constraint. It is shown that the first-order optimality condition of the nonlinear programming problem associ...

We consider the problem of minimizing a convex separable logarithmic function over a region defined by a convex inequality constraint or linear equality constraint, and twosided bounds on the variables (box constraints). Such problems are interesting from both theoretical and practical point of view because they arise in somemathematical programming problems as well as in various practical prob...

In this paper, we design a multi-objective controller ( ) u t to achieve the following three objectives simultaneously. They are pole placement, H∞ norm constraint and individual error state variance constraint for stochastic model reference systems. By using the invariance property of sliding mode control, the matched model reference input and the plant error term will disappear on the sliding...

In this paper, the problem of designing fixed-order robustH∞ controllers is considered for linear systems affected by polytopic uncertainty. A polynomial method is employed to design a fixed-order controller that guarantees that all the closed-loop poles reside within a given region of the complex plane. In order to utilise the freedom of the controller design, an H∞ performance specification i...

The mechanical unfolding of a set of 12 proteins with diverse topologies is investigated using an all-atom constraint-based model. Proteins are represented as polypeptides cross-linked by hydrogen bonds, salt bridges, and hydrophobic contacts, each modeled as a harmonic inequality constraint capable of supporting a finite load before breaking. Stereochemically acceptable unfolding pathways are ...

Quadratic constraints on the weight vector of an adaptive linearly constrained minimum power (LCMP) beamformer can improve robustness to pointing errors and to random perturbations in sensor parameters. In this paper, we propose a technique for implementing a quadratic inequality constraint with recursive least squares (RLS) updating. A variable diagonal loading term is added at each step, wher...

We present a Bayesian CAD modeler for robotic applications. We describe the methodology we use to represent and handle uncertainties using probability distributions on the system parameters and sensor measurements. We address the problem of the propagation of geometric uncertainties and how to take this propagation into account when solving inverse problems. The proposed approach may be seen as...

We consider a multiobjective optimization problem with a feasible set defined by inequality and equality constraints such that all functions are, at least, Dini differentiable (in some cases, Hadamard differentiable and sometimes, quasiconvex). Several constraint qualifications are given in such a way that generalize both the qualifications introduced by Maeda and the classical ones, when the f...