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Browsing Cognitive & Neural Systems by Title

OpenBU

Browsing Cognitive & Neural Systems by Title

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  • Carpenter, Gail A.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
  • 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 ...
  • Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-03)
    The distributed outstar, a generalization of the outstar neural network for spatial pattern learning, is introduced. In the outstar, signals from a source node cause weights to learn and recall arbitrary patterns across a ...
  • Grossberg, Stephen; Yazdanbakhsh, Arash; Swaminathan, Guru; Cao, Yongqiang (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2006-10)
    Under natural viewing conditions, a single depthful percept of the world is consciously seen. When dissimilar images are presented to corresponding regions of the two eyes, binocular rivalry may occur, during which the ...
  • Tan, Can Ozan; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-02)
    The "teaching signal" that modulates reinforcement learning at cortico-striatal synapses may be a sequence composed of an adaptively scaled DA burst, a brief ACh burst, and a scaled ACh pause. Such an interpretation is ...
  • Dranias, Mark R.; Grossberg, Stephen; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-12)
    Animals are motivated to choose environmental options that can best satisfy current needs. To explain such choices, this paper introduces the MOTIVATOR (Matching Objects To Internal Values Triggers Option Revaluations) ...
  • Williamson, James (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    Recognition of objects in complex visual scenes is greatly simplified by the ability to segment features belonging to different objects while grouping features belonging to the same object. This feature-binding process can ...
  • Bradski, Gary (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1992-02)
    This paper demonstrates an optimal control solution to change of machine set-up scheduling based on dynamic programming average cost per stage value iteration as set forth by Cararnanis et. al. [2] for the 2D case. The ...
  • Viswanathan, Lavanya; Mingolla, Ennio (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-04)
    The allocation of attention in depth is examined using a multi-element tracking paradigm. Observers are required to track a predefined subset of from two to eight elements in displays containing up to sixteen identical ...
  • Berzhanskaya, Julia; Swaminathan, Gurumurthy; Beck, Jacob; Mingolla, Ennio (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-02)
    The perception of a glossy surface in a static monochromatic image can occur when a bright highlight is embedded in a compatible context of shading and a bounding contour. Some images naturally give rise to the impression ...
  • Przybyszewski, A.W.; Sucher, N.J.; Grüsser, O.-J. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-01)
    L(+)-, D(-)-, or DL-2-amino-4-phosphonobutyric acid (APB; 2.5- 16 μmol) were injected into the vitreous body of anesthetized adult cats. The retina was stimulated by diffuse square wave light flashes (10- 60 ms). The ...
  • Gonsalves, Paul G.; Snorrason, Magnus; Caglayan, Alper K. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    Training data for supervised learning neural networks can be clustered such that the input/output pairs in each cluster are redundant. Redundant training data can adversely affect training time. In this paper we apply two ...
  • Bullock, Dan; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    The origin of the tri-phasic burst pattern, observed in the EMGs of opponent muscles during rapid self-terminated movements, has been controversial. Here we show by computer simulation that the pattern emerges from ...
  • Bullock, Daniel; Contreras-Vidal, José L.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1992-02)
    One of the advantages of biological skeleto-motor systems is the opponent muscle design, which in principle makes it possible to achieve facile independent control of joint angle and joint stiffness. Prior analysis of ...
  • Wagner, Robert; Polimeni, Jonathan; Schwartz, Eric (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-12)
    Log-polar image architectures, motivated by the structure of the human visual field, have long been investigated in computer vision for use in estimating motion parameters from an optical flow vector field. Practical ...
  • Carpenter, Gail A.; Govindarajan, Krishna (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    A procedure that uses fuzzy ARTMAP and K-Nearest Neighbor (K-NN) categorizers to evaluate intrinsic and extrinsic speaker normalization methods is described. Each classifier is trained on preprocessed, or normalized, vowel ...
  • Balasubramanian, Mukund; Polimeni, Jonathan R.; Schwartz, Eric L. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-12)
    We present two algorithms for computing distances along a non-convex polyhedral surface. The first algorithm computes exact minimal-geodesic distances and the second algorithm combines these distances to compute exact ...
  • Araki, Osamu (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-05)
    We can recognize objects through receiving continuously huge temporal information including redundancy and noise, and can memorize them. This paper proposes a neural network model which extracts pre-recognized patterns ...
  • Santini, Fabrizio; Redner, Gabriel; Rucci, Michele (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-12)
  • Santini, Fabrizio; Redner, Gabriel; Lovin, Ramon; Rucci, Michele (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2005-09)
    In experimental studies of visual performance, the need often emerges to modify the stimulus according to the eye movements perfonncd by the subject. The methodology of Eye Movement-Contingent Display (EMCD) enables accurate ...

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