Browsing Cognitive & Neural Systems by Subject "Adaptive resonance theory"

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Browsing Cognitive & Neural Systems by Subject "Adaptive resonance theory"

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  • Adaptive Resonance: An Emerging Neural Theory of Cognition
    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, ...
  • Adaptive Resonance Theory: Self-Organizing Networks for Stable Learning, Recognition, and Prediction
    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 ...
  • AIRSTREAM: A Neural Network Model of Auditory Scene Analysis and Source Segregation
    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 ...
  • ART-EMAP: A Neural Network Architecture for Object Recognition by Evidence Accumulation
    Carpenter, Gail A.; Ross, William D. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-10)
    A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and 3-D object ...
  • ARTMAP-IC and Medical Diagnosis: Instance Counting and Inconsistent Cases
    Carpenter, Gail A.; Markuzon, Natalya (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-05)
    For complex database prediction problems such as medical diagnosis, the ARTMAP-IC neural network adds distributed prediction and category instance counting to the basic fuzzy ARTMAP system. For the ARTMAP match tracking ...
  • ARTMAP: Supervised Real-Time Learning and Classification of Nonstationary Data by a Self-Organizing Neural Network
    Carpenter, Gail A.; Grossbergy, Stephen; Reynolds, John (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This ...
  • ART Neural Networks: Distributed Coding and ARTMAP Applications
    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 ...
  • Beta Oscillations and Hippocampal Place Cell Learning during Exploration of Novel Environments
    Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2008-07-29)
    Berke et al. (2008) reported that beta oscillations occur during the learning of hippocampal place cell receptive fields in novel environments. Place cell selectivity can develop within seconds to minutes, and can remain ...
  • Biased ART: A Neural Architecture that Shifts Attention Toward Previously Disregarded Features Following an Incorrect Prediction
    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 ...
  • Cortical Learning of Recognition Categories: A Resolution of the Exemplar Vs. Prototype Debate
    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? ...
  • Distributed Learning, Recognition, and Prediction by ART and ARTMAP Neural Networks
    Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-01)
    A class of adaptive resonance theory (ART) models for learning, recognition, and prediction with arbitrarily distributed code representations is introduced. Distributed ART neural networks combine the stable fast learning ...
  • Fuzzy ART: Fast Stable Learning and Categorization of Analog Patterns by an Adaptive Resonance System
    Carpenter, Gail; Grossberg, Stephen; Rosen, David (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-06)
    A Fuzzy ART model capable of rapid stable learning of recognition categories in response to arbitrary sequences of analog or binary input patterns is described. Fuzzy ART incorporates computations from fuzzy set theory ...
  • Gaussian Artmap: A Neural Network for Fast Incremental Learning of Noisy Multidimensional Maps
    Williamson, James R. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-02)
    A new neural network architecture for incremental supervised learning of analalog multidimensional maps is introduced. The architecture, called Gaussian ARTMAP, is a synthesis of a Gaussian classifier and an Adaptive ...
  • How Hallucinations May Arise from Brain Mechanisms of Learning, Attention, and Volition
    Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-07)
    This article suggests how brain mechanisms of learning, attention, and volition may give rise to hallucinations during schizophrenia and other mental disorders. The article suggests that normal learning and memory are ...
  • Neural Dynamics of Variable Rate Speech Categorization
    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 ...
  • A Neural Network Model of Auditory Scene Anaysis and Source Segregation
    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 ...
  • A Neural Network Realization of Fuzzy ART
    Carpenter, Gail A.; Grossberg, Stephen; Rosen, David B. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-08)
    A neural network realization of the fuzzy Adaptive Resonance Theory (ART) algorithm is described. Fuzzy ART is capable of rapid stable learning of recognition categories in response to arbitrary sequences of analog or ...
  • A Self-Organizing Neural System for Learning to Recognize Textured Scenes
    Grossberg, Stephen; Williamson, James (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-01)
    A self-organizing ARTEX model is developed to categorize and classify textured image regions. ARTEX specializes the FACADE model of how the visual cortex sees, and the ART model of how temporal and prefrontal cortices ...
  • Spikes, Synchrony, and Attentive Learning by Laminar Thalamocortical Circuits
    Grossberg, Stephen; Versace, Massimiliano (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-12)
  • Texture Segregation By Visual Cortex: Perceptual Grouping, Attention, and Learning
    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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