Computer Intensive Methods in Control and Signal Processing: The Curse of Dimensionality
Generate an AI Snapshot to get a quick, structured summary of this paper.
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
Fighting dimensionality with linguistic geometry, Boris Stilman Statistical physics and the optimization of autonomous behaviour in complex virtual worlds, Robert W. Penney On merging gradient estimation with mean-tracking techniques for cluster identification, Paul D. Fox et al Computational aspects of graph theoretic methods in control, Katalin M. Hangos, Zsolt Tuza Efficient algorithms for predictive control of systems with bounded inputs, Luigi Chisci et al Applying new numerical algorithms to the solution of discrete-time optimal control problems, Rudiger Franke, Eckhard Arnold System identification using composition networks, Yves Moreau, Joos Vandewalle Recursive nonlinear estimation of non-linear/non-Gaussian dynamic models, Rudolf Kulhavy Monte Carlo approach to Bayesian regression modelling, Jan Smid et al Identification of reality in Bayesian context, Ludek Berec, Miroslav Karny Nonlinear nonnormal dynamic models - state estimation and software, Miroslav Simandl, Miroslav Flidr The EM algorithm - a guided tour, Christophe Couvreur estimation of quasipolynomilas in noise - theoretical algorithmic and implementation aspects, Vytautas Slivinskas, Virginija Simonyte Iterative reconstruction of transmission sinograms with low signal to noise ratio, Johan Nuyts et al Curse of dimensionality - classifying large multi-dimensional images with neural networks, Rudolf Hanka, Thomas P. Harte Dimension-independent rates of approximation by neural networks, Vera Kurkova estimation of human signal detection performance from event-related potentials using feed-forward neural network model, Milos Koska et al Utilizing geometric anomalies of high dimension - when complexity makes computation easier, Paul C. Kainen Approximation using cubic B-splines with improved training speed and accuracy, Julian D. Mason et al.
