Results 1 - 10 of 2,932

A Model of Saliency-based Visual Attention for Rapid Scene Analysis

by Laurent Itti, Christof Koch, Ernst Niebur , 1998
"... A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing salie ..."
Abstract - Cited by 1748 (72 self) - Add to MetaCart
A visual attention system, inspired by the behavior and the neuronal architecture of the early primate visual system, is presented. Multiscale image features are combined into a single topographical saliency map. A dynamical neural network then selects attended locations in order of decreasing

Randomized kinodynamic planning

by Steven M. Lavalle, James J. Kuffner, Jr. - THE INTERNATIONAL JOURNAL OF ROBOTICS RESEARCH 2001; 20; 378 , 2001
"... This paper presents the first randomized approach to kinodynamic planning (also known as trajectory planning or trajectory design). The task is to determine control inputs to drive a robot from an initial configuration and velocity to a goal configuration and velocity while obeying physically based ..."
Abstract - Cited by 626 (35 self) - Add to MetaCart
dynamical models and avoiding obstacles in the robot’s environment. The authors consider generic systems that express the nonlinear dynamics of a robot in terms of the robot’s high-dimensional configuration space. Kinodynamic planning is treated as a motion-planning problem in a higher dimensional state

Control of Systems Integrating Logic, Dynamics, and Constraints

by Alberto Bemporad, Manfred Morari - Automatica , 1998
"... This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as Mixed Logical Dynamical (MLD) systems. These are described by linear dynamic equations subject to linear inequalities involving real and ..."
Abstract - Cited by 413 (50 self) - Add to MetaCart
This paper proposes a framework for modeling and controlling systems described by interdependent physical laws, logic rules, and operating constraints, denoted as Mixed Logical Dynamical (MLD) systems. These are described by linear dynamic equations subject to linear inequalities involving real

Harnessing nonlinearity: Predicting chaotic systems and saving energy in wireless communication

by Herbert Jaeger, Harald Haas - Science , 2004
"... We present a method for learning nonlinear systems, echo state networks (ESNs). ESNs employ artificial recurrent neural networks in a way that has recently been proposed independently as a learning mechanism in biological brains. The learning method is computationally efficient and easy to use. On a ..."
Abstract - Cited by 285 (16 self) - Add to MetaCart
We present a method for learning nonlinear systems, echo state networks (ESNs). ESNs employ artificial recurrent neural networks in a way that has recently been proposed independently as a learning mechanism in biological brains. The learning method is computationally efficient and easy to use

Nonlinear Black-Box Modeling in System Identification: a Unified Overview

by Jonas Sjöberg, Qinghua Zhang, Lennart Ljung, Albert Benveniste, Bernard Deylon, Pierre-yves Glorennec, Hakan Hjalmarsson, Anatoli Juditsky - Automatica , 1995
"... A nonlinear black box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area with structures based on neural networks, radial basis networks, wavelet networks, hinging hyperplanes, ..."
Abstract - Cited by 225 (16 self) - Add to MetaCart
A nonlinear black box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area with structures based on neural networks, radial basis networks, wavelet networks, hinging hyperplanes

Contour enhancement, short-term memory, and constancies in reverberating neural networks

by Stephen Grossberg - Studies in Applied Math , 1973
"... A model of the nonlinear dynamics of reverberating on-center off-surround networks of nerve cells, or of cell populations, is analysed. The on-center off-surround anatomy allows patterns to be processed across populations without saturating the populations ' response to large inputs. The signal ..."
Abstract - Cited by 245 (93 self) - Add to MetaCart
A model of the nonlinear dynamics of reverberating on-center off-surround networks of nerve cells, or of cell populations, is analysed. The on-center off-surround anatomy allows patterns to be processed across populations without saturating the populations ' response to large inputs

Modelling gene expression data using dynamic bayesian networks

by Kevin Murphy, Saira Mian , 1999
"... Recently, there has been much interest in reverse engineering genetic networks from time series data. In this paper, we show that most of the proposed discrete time models — including the boolean network model [Kau93, SS96], the linear model of D’haeseleer et al. [DWFS99], and the nonlinear model of ..."
Abstract - Cited by 223 (1 self) - Add to MetaCart
Recently, there has been much interest in reverse engineering genetic networks from time series data. In this paper, we show that most of the proposed discrete time models — including the boolean network model [Kau93, SS96], the linear model of D’haeseleer et al. [DWFS99], and the nonlinear model

How does a brain build a cognitive code

by Stephen Grossberg - Psychological Review , 1980
"... This article indicates how competition between afferent data and learned feedback expectancies can stabilize a developing code by buffering committed populations of detectors against continual erosion by new environmental demands. Tille gating phenomena that result lead to dynamically maintained cri ..."
Abstract - Cited by 253 (94 self) - Add to MetaCart
]lliculo-occipital waves; olfactory coding, corticogeniculate feedback, matching of proprioceptive and terminal motor maps, and cerebral dominance. The psychophysiological mechanisms that unify these effects are inherently nonlinear and parallel and are inequivalent to the computer, probabilistic, and linear models

Selforganized control of bipedal locomotion by neural oscillators in unpredictable environment. Biol. Cybern

by G. Taga, Y. Yamaguehi, H. Shimizu , 1991
"... Abstract. A new principle of sensorimotor control of legged locomotion in an unpredictable environment is proposed on the basis of neurophysiological knowledge and a theory of nonlinear dynamics. Stable and flexible locomotion is realized as a global limit cycle generated by a global entrainment bet ..."
Abstract - Cited by 179 (2 self) - Add to MetaCart
Abstract. A new principle of sensorimotor control of legged locomotion in an unpredictable environment is proposed on the basis of neurophysiological knowledge and a theory of nonlinear dynamics. Stable and flexible locomotion is realized as a global limit cycle generated by a global entrainment

A trajectory piecewise-linear approach to model order reduction and fast simulation of nonlinear circuits and micromachined devices

by Jacob White, Associate Member - in Proc. Int. Conf. Computer-Aided Design
"... Abstract—In this paper, we present an approach to nonlinear model reduction based on representing a nonlinear system with a piecewise-linear system and then reducing each of the pieces with a Krylov projection. However, rather than approximating the individual components as piecewise linear and then ..."
Abstract - Cited by 144 (8 self) - Add to MetaCart
the fly, ” to accelerate simulation of the system response. Index Terms—Microelectromechanical systems (MEMS), model order reduction, nonlinear analog circuits, nonlinear dynamical systems, piecewise-linear models. I.
Results 1 - 10 of 2,932