Geometric optimization of dielectric elastomer electrodes for dynamic applications
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We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solutio ...
This paper describes a system to drive piezoelectric actuators over more than one decade of voltages and one octave of frequencies, in order to perform high-speed complex impedance characterization at a user chosen voltage excitation level. This characteri ...
This thesis is about the numerical simulation and optimization of the alumina repartition in the bath of an aluminium electrolysis pot. A mathematical model is set up which contains the feeding of alumina particles to the bath, the dissolution of the parti ...
Many state-of-the-art approaches for Multi Kernel Learning (MKL) struggle at finding a compromise between performance, sparsity of the solution and speed of the optimization process. In this paper we look at the MKL problem at the same time from a learning ...
Many state-of-the-art approaches for Multi Kernel Learning (MKL) struggle at finding a compromise between performance, sparsity of the solution and speed of the optimization process. In this paper we look at the MKL problem at the same time from a learning ...
In multivariate systems, when it comes to identifying actual operating conditions ranges, or optimal settings, the use of constrained optimization is often required. Among the different tools for the engineer to perform such optimization, designed experime ...
This work presents a synthesis method that leads to the preliminary design of industrial energy systems. Such systems are composed of several technologies that transform, through a set of physical unit operations, raw materials and energy into products and ...
This paper presents a new paradigm in the design of indoor flying robots that replaces collision avoidance with collision robustness. Indoor flying robots must operate within constrained and cluttered environments where even nature’s most sophisticated fly ...
An iterative procedure for the synthesis of sparse arrays radiating focused or shaped beampattern is presented. The algorithm consists in solving a sequence of weighted l(1) convex optimization problems. The method can thus be readily implemented and effic ...
Institute of Electrical and Electronics Engineers2012
The optimization of k-space sampling for nonlinear sparse MRI reconstruction is phrased as Bayesian experimental design problem. Bayesian inference is approximated by a novel relaxation to standard signal processing primitives, resulting in an efficient op ...