Browsing Cognitive & Neural Systems by Author "Gaudiano, Paolo"

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Browsing Cognitive & Neural Systems by Author "Gaudiano, Paolo"

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  • Chang, Caroilna; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-02)
    We present a neural network that learns to control approach and avoidance behaviors in a mobile robot using the mechanisms of classical and operant conditioning. Learning, which requires no supervision, takes place as the ...
  • Streilein, William W.; Gaudiano, Paolo; Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-05)
    ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic mapping from satellite remote sensing data, machine tool ...
  • Streilein, William W.; Gaudiano, Paolo; Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-05)
    ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic mapping from satellite remote sensing data, machine tool ...
  • Pedini, David; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-08)
    The Adaptive Resonance Theory (ART) architecture, first proposed by (Grossberg, 1976b, 1976a), is a self-organizing neural network for stable pattern categorization in response to arbitrary input sequences. Since its ...
  • Sahin, Erol; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-02)
    This article describes and evaluates visual looming as a monocular range sensing method for mobile robots. The looming algorithm is based on the relationship between the displacement of a camera relative to an object, and ...
  • Martens, Siegfried; Gaudiano, Paolo; Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-03)
    The raw sensory input available to a mobile robot suffers from a variety of shortcomings. Sensor fusion can yield a percept more veridical than is available from any single sensor input. In this project, the fuzzy ARTMAP ...
  • Gaudiano, Paolo; Zalama, Eduardo; Coronado, Juan Lopez (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-04)
    We have recently introduced a self-organizing adaptive neural controller that learns to control movements of a wheeled mobile robot toward stationary or moving targets, even when the robot's kinematics arc unknown, or when ...
  • Dorman, Clark; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-06)
    The ability of humans and animals to survive in a constantly changing environment is a testament to the power of biological processes. At any given instant in our lives, we are faced with an enormous number of sensory ...
  • Chey, Jonathan; Cisek, Paul; Gaudiano, Paolo; Wood, Richard J. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-10)
    A long-term bias in the exploratory head-waving behavior of Aplysia can be induced using bright lights as an aversive stimulus: coupling onset of the lights with head movements to one side results in a bias away from that ...
  • Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    This article introduces a quantitative model of early visual system function. The model is formulated to unify analyses of spatial and temporal information processing by the nervous system. Functional constraints of the ...
  • Martens, Siegfried; Carpenter, Gail A.; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-08)
    An ARTMAP neural network is used to integrate visual information and ultrasonic sensory information on a B 14 mobile robot. Training samples for the neural network are acquired without human intervention. Sensory snapshots ...
  • Gaudiano, Paolo; Mejia-Monasterio, Norma (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-04)
  • Zalana, Eduardo; Gaudiano, Paolo; Coronado, Juan Lopez (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-01)
    This article introduces a real-time, unsupervised neural network that learns to control a two-degree-of-freedom mobile robot in a nonstationary environment. The neural controller, which is termed neural NETwork MObile Robot ...
  • Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-07)
    This article describes a nonlinear model of neural processing in the vertebrate retina, comprising model photoreceptors, model push-pull bipolar cells, and model ganglion cells. Previous analyses and simulations have shown ...
  • Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1992-07)
    A computational model of visual processing in the vertebrate retina provides a unified explanation of a range of data previously treated by disparate models. Three results are reported here: the model proposes a functional ...
  • Gaudiano, Paolo; Zalama, Eduardo; Coronado, Juan Lopez (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-06)
    We have recently introduced a neural network mobile robot controller (NETMORC). The controller is based on earlier neural network models of biological sensory-motor control. We have shown that NETMORC is able to guide a ...
  • Gaudiano, Paolo; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    This article describes neural network models for adaptive control of arm movement trajectories during visually guided reaching and, more generally, a framework for unsupervised real-time error-based learning. The models ...
  • Sahin, Erol; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-02)
    This paper describes and evaluates visual looming as a method for monocular range estimation. The looming algorithm is based on the relationship between displacements of the observer relative to an object, and the resulting ...

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