Browsing CAS/CNS Technical Reports by Title

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Browsing CAS/CNS Technical Reports by Title

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  • Granger, Eric; Grossberg, Stephen; Rubin, Mark; Streilein, William (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-07)
    The ARTMAP-FD neural network performs both identification (placing test patterns in classes encountered during training) and familiarity discrimination (judging whether a test pattern belongs to any of the classes encountered ...
  • Rubin, Mark (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-02)
    We obtain a bound on the expected error rate of the fuzzy ARTMAP neural network employed as a classifier. This bound is based on leave-one-out estimation of the classification error, and is analogous to a bound on the ...
  • Contreras-Vidal, José L.; Aguilar, Mario (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-05)
    A fast and efficient segmentation algorithm based on the Boundary Contour System/Feature Contour System (BCS/FCS) of Grossberg and Mingolla [3] is presented. This implementation is based on the FFT algorithm and the ...
  • 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 ...
  • Yazdanbakhsh, Arash; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-06-08)
    Perceptual grouping is well-known to be a fundamental process during visual perception, notably grouping across scenic regions that do not receive contrastive visual inputs. Illusory contours are a classical example of ...
  • Williamson, James (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-05)
    A model of cortical learning is proposed, which incorporates supervised feedback using two forms of attention: (i) feature-specific attention which allows the network to learn associations between specific feature conjunctions ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-09)
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-02)
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-10)
  • Rucci, Michele; Casile, Antonio (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-12)
    Under natural viewing conditions small movements of the eye, head, and body prevent the maintenance of a steady direction of gaze. It is known that stimuli tend to fade when they a restabilized on the retina for several ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-12)
  • Cohen, Michael A.; Grossberg, Stephen; Pribe, Christopher A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    The 2-channel Ellias-Grossberg neural pattern generator of Cohen, Grossberg, and Pribe [1] is shown to simulate data from human bimanual coordination tasks in which anti-phase oscillations at low frequencies spontaneously ...
  • Okatan, Murat; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-01)
    Experiments by Markram and Tsodyks (1996) have suggested that Hebbian pairing in cortical pyramidal neurons potentiates or depresses the transmission of a subsequent presynaptic spike train al steady-state depending on ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-01)
  • Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-05)
    Calligraphic writing presents a rich set of challenges to the human movement control system. These challenges include: initial learning, and recall from memory, of prescribed stroke sequences; critical timing of stroke ...
  • Fang, Liang; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2006-12-12)
    When we look at a scene, how do we consciously see surfaces infused with lightness and color at the correct depths? Random Dot Stereograms (RDS) probe how binocular disparity between the two eyes can generate such conscious ...
  • Grossberg, Stephen; Versace, Massimiliano (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2006-12-06)
    How do our brains transform the "blooming buzzing confusion" of daily experience into a coherent sense of self that can learn and selectively attend to important information? How do local signals at multiple processing ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-03)
    Neural models have proposed how short-term memory (STM) storage in working memory and long-term memory (LTM) storage and recall are linked and interact, but are realized by different mechanisms that obey different laws. ...
  • Asfour, Yousif R.; Carpenter, Gail A.; Grossberg, Stephen; Lesher, Gregory W. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-08)
    Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi-sensor, data fusion. Fusion ARTMAP generalizes the fuzzy ARTMAP architecture in order to adaptively classify multi-channel data. ...
  • Asfour, Yousif R.; Carpenter, Gail A.; Grossberg, Stephen; Lesher, Gregory (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    Fusion ARTMAP is a self-organizing neural network architecture for multi-channel, or multi-sensor, data fusion. Single-channel Fusion ARTMAP is functionally equivalent to Fuzzy ART during unsupervised learning and to Fuzzy ...

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