The parameter perturbation methods (the most known being the OGY method) apply small wisely chosen swift kicks to the system once per cycle, to maintain it near the desired unstable periodic orbit. Thus, one can consider that a new attractor is finally generated. Another class of methods which allow the attractors born, imply small perturbations of the state variable [see, e.g., J. Güémez and M...

An intelligent audio system for sound design using artificial intelligence techniques is reported. The system is used to analyse acoustic recordings, extract salient sound features and to process them to generate parameters for sound synthesis, in a manner that mimics human audio experts. Preliminary tests show that the use of the system reduces design time and yet the quality of the resulting ...

We present a parameter synthesis algorithm for planar, higher pair mechanical systems. The input is a parametric model of a mechanical system (part shapes and configurations) with nominal values and tolerance intervals for the parameters. The output is revised parameter ranges that guarantee correct kinematic function for all system variations. Nominal values are changed when possible and toler...

We propose a symbolic method to synthesise optimal values of timing parameters for probabilistic timed automata, in the sense that the probability of reaching some set of states is either maximised or minimised. Our first algorithm, based on forward exploration of the symbolic states, can only guarantee parameter values that correspond to upper (resp. lower) bounds on maximum (resp. minimum) re...

My intention in this paper is to outline and motivate a novel theory of syntactic bootstrapping, Exemplar-Based Phonological Bootstrapping (EBPB), based on Stochastic Tree-Substitution Grammar. Because I have outlined the basic structure of STSG in other places for assessed work on this degree, I will not recapitulate that work in the body of the present paper, but will instead quote it in full...

Technical systems interacting with the real world can be elegantly modelled using probabilistic hybrid automata (PHA). Parametric probabilistic hybrid automata are dynamical systems featuring hybrid discrete-continuous dynamics and parametric probabilistic branching, thereby generalizing PHA by capturing a family of PHA within a single model. Such systems have a broad range of applications, fro...

Novel applications of formal modelling such as systems biology have highlighted the need to extend formal analysis techniques to domains with pervasive parametric uncertainty. Consequently, machine learning methods for parameter synthesis and uncertainty quantification are playing an increasingly significant role in quantitative formal modelling. In this paper, we introduce a toolbox for parame...

Parameterized Lyapunov bounds and shifted quadratic guaranteed cost bounds are merged to develop shifted parameter-dependent quadratic cost bounds for robust stability and robust performance. Robust fixed-order (i.e., fulland reduced-order) controllers are developed based on new shifted parameter-dependent bounding functions. A numerical example is presented to demonstrate the effectiveness of ...

The dynamics of biological processes are often modeled as systems of nonlinear ordinary differential equations (ODE). An important feature of nonlinear ODEs is that seemingly minor changes in initial conditions or parameters can lead to radically different behaviors. This is problematic because in general it is never possible to know/measure the precise state of any biological system due to mea...

In this paper, we consider discrete-time continuous-space Piecewise Affine (PWA) systems with parameter uncertainties, and study temporal logic properties of their trajectories. Specifically, given a PWA system with polytopal parameter uncertainties, and a Linear Temporal Logic (LTL) formula over linear predicates in the states of the system, we attempt to find subsets of parameters guaranteein...