Browsing Cognitive & Neural Systems by Subject "art"

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Browsing Cognitive & Neural Systems by Subject "art"

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  • Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-09)
    Adaptive resonance is a theory of cognitive information processing which has been realized as a family of neural network models. In recent years, these models have evolved to incorporate new capabilities in the cognitive, ...
  • Carpenter, Gail; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-05)
    Adaptive Resonance Theory (ART) is a neural theory of human and primate information processing and of adaptive pattern recognition and prediction for technology. Biological applications to attentive learning of visual ...
  • Grossberg, Stephen; Govindarajan, Krishna; Wyse, Lonce; Cohen, Michael (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-06)
    Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an "auditory ...
  • Carpenter, Gail A.; Grossberg, Stephen; Rosen, David (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    This article introduces ART 2-A, an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART 2 neural network architecture, but at a speed two to three orders ...
  • 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 ...
  • Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-03)
    ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include airplane design and manufacturing, automatic target recognition, financial ...
  • Carpenter, Gail A.; Gaddam, Sai Chaitanya (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2009-04)
    Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved ...
  • Amis, Gregory P.; Carpenter, Gail A.; Ersoy, Bilgin; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2009-03)
    Do humans and animals learn exemplars or prototypes when they categorize objects and events in the world? How are different degrees of abstraction realized through learning by neurons in inferotemporal and prefrontal cortex? ...
  • Carpenter, Gail A.; Milenova, Boriana L.; Noeske, Benjamin W. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-12)
    Distributed coding at the hidden layer of a multi-layer perceptron (MLP) endows the network with memory compression and noise tolerance capabilities. However, an MLP typically requires slow off-line learning to avoid ...
  • Bradski, Gary; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-08-01)
    The recognition of 3-D objects from sequences of their 2-D views is modeled by a family of self-organizing neural architectures, called VIEWNET, that use View Information Encoded With NETworks. VIEWNET incorporates a ...
  • Carpenter, Gail A.; Grossberg, Stephen; Reynolds, John H. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-10)
    An incremental, nonparametric probability estimation procedure using the fuzzy ARTMAP neural network is introduced. In slow-learning mode, fuzzy ARTMAP searches for patterns of data on which to build ever more accurate ...
  • Grossberg, Stephen; Boardman, Ian; Cohen, Michael (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-12)
    What is the neural representation of a speech code as it evolves in real time? A neural model of thiss process, called the ARTPHONE model, is developed to quantitatively simulate data concerning segregation and integration ...
  • Govindarajan, Krishna; Grossberg, Stephen; Wyse, Lonce; Cohen, Michael (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-12)
    In environments with multiple sound sources, the auditory system is capable of teasing apart the impinging jumbled signal into different mental objects, or streams, as in its ability to solve the cocktail party problem. A ...
  • Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-10)
  • Bhatt, Rushi; Carpenter, Gail A.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2006-07-28)
    A neural model is proposed of how laminar interactions in the visual cortex may learn and recognize object texture and form boundaries. The model brings together five interacting processes: region-based texture classification, ...

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