Browsing Cognitive & Neural Systems by Subject "Neural network"

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Browsing Cognitive & Neural Systems by Subject "Neural network"

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  • Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-09)
    Temporal structure in skilled, fluent action exists at several nested levels. At the largest scale considered here, short sequences of actions that are planned collectively in prefrontal cortex appear to be queued for ...
  • 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.; 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 ...
  • 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 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 ...
  • Shock, Byron; Carpenter, Gail; Gopal, Sucharita; Woodcock, Curtis (Boston University Computer Science Department, 2001-12)
    The ability to detect and monitor changes in land use is essential for assessment of the sustainability of development. In the next decade, NASA will gather high-resolution multi-spectral and multi-temporal data, which ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-01)
    The processes whereby our brains continue to learn about a changing world in a stable fashion throughout life are proposed to lead to conscious experiences. These processes include the learning of top-down expectations, ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-09)
    How do our brains so effectively achieve adaptive behavior in a changing world? Evidence is reviewed that brains are organized into parallel processing streams with complementary properties. Hierarchical interactions within ...
  • Raizada, Rajeev; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-07)
    A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-05)
    This article develops the FACADE theory of 3-D vision and figure-ground separation to explain data concerning how 2-D pictures give rise to 3-D percepts of occluding and occluded objects. These percepts include pop-out of ...
  • Grossberg, Stephen; McLoughlin, Niall (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-07)
    Previous models of stereopsis have concentrated on the task of binocularly matching left and right eye primitives uniquely. A disparity smoothness constraint is often invoked to limit the number of possible matches. These ...
  • Francis, Gregory; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-01)
    Using a neural network model of boundary segmentation and reset, Francis, Grossberg, and Mingolla (1994) linked the percept of persistence to the duration of a boundary segmentation after stimulus offset. In particular, ...
  • Grossbergy, Stephen; Rudd, Michael E. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-04)
    This article describes further evidence for a new neural network theory of biological motion perception. The theory clarifies why parallel streams Vl --> V2, Vl --> MT, and Vl --> V2 --> MT exist for static form and motion ...
  • Grossberg, Stephen; Gruenwald, Alexander (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-05)
    How does the brain group together different parts of an object into a coherent visual object representation? Different parts of an object may be processed by the brain at different rates and may thus become desynchronized. ...
  • Cisek, Paul; Grossberg, Stephen; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-11)
    A model of cortico-spinal trajectory generation for voluntary reaching movements is developed to functionally interpret a broad range of behavioral, physiological and anatomical data. The model simulates how arm movements ...
  • 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 ...
  • van Heijst, J.J.; Vos, J.E.; Bullock, D. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-11)
    In two phases, we develop neural network models of spinal circuitry which self-organises into networks with opponent channels for the control of an antagonistic muscle pair. The self-organisation is enabled by spontaneous ...

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