Browsing College of Arts and Sciences by Title

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Browsing College of Arts and Sciences by Title

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  • Tsang, Aaron (2012-07-13)
    This paper explores the transformation of business interest organization in South Korea and Taiwan. I would explore how the state, capital, and labor respond to the currents of democratization and economic liberalization ...
  • 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 ...
  • Weller, Robert; Li, Jiansheng (The University of Chicago Press, 2013-01-24)
  • 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. ...
  • Ratnam, Karunaharan; Matta, Ibrahim; Rangarajan, Sampath (Boston University Computer Science Department, 1999-08-24)
    In [previous papers] we presented the design, specification and proof of correctness of a fully distributed location management scheme for PCS networks and argued that fully replicating location information is both appropriate ...
  • 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 ...
  • Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-12-15)
    Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP synthesize fuzzy logic and ART networks ...
  • Carpetner, Gail A.; Grossberg, Stephen; Rosen, David B. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    The Fuzzy ART system introduced herein incorporates computations from fuzzy set theory into ART 1. For example, the intersection (n) operator used in ART 1 learning is replaced by the MIN operator (A) of fuzzy set theory. ...
  • Carpenter, Gail A.; Gjaja, Marin N. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-12)
    Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP networks synthesize fuzzy logic and ART ...
  • 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 ...
  • Carpenter, Gail A.; Grossberg, Stephen; Markuzon, Natalya; Reynolds, John H.; Rosen David B. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-08)
    A new neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors. The architecture, ...
  • 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 ...
  • Carpenter, Gail A.; Grossberg, Stephen; Reynolds, John H. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    A nonparametric probability estimation procedure using the fuzzy ARTMAP neural network is here described. Because the procedure does not make a priori assumptions about underlying probability distributions, it yields ...
  • Przybyszewski, Andrzej W.; Rubin, Mark A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-05)
    Anatomical studies have documented massive back-projections from higher to lower visual cortices and to the lateral geniculate nucleus (LGN). The large number of synapses from these sources suggest that they should have a ...
  • 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 ...
  • Papapetrou, Panagiotis; Benson, Gary; Kollios, George (Boston University Computer Science Department, 2008-10-21)
    The problem of discovering frequent poly-regions (i.e. regions of high occurrence of a set of items or patterns of a given alphabet) in a sequence is studied, and three efficient approaches are proposed to solve it. The ...

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