Browsing CAS/CNS Technical Reports by Title

OpenBU

Browsing CAS/CNS Technical Reports by Title

Sort by: Order: Results:

  • Carpenter, Gail A.; Ross, William D. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-11)
    ART-EMAP synthesizes adaptive resonance theory (AHT) and spatial and temporal evidence integration for dynamic predictive mapping (EMAP). The network extends the capabilities of fuzzy ARTMAP in four incremental stages. ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-05)
    A neural network theory of :3-D vision, called FACADE Theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations ...
  • Johnson, Dave; Guenther, Frank H. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-03)
    Recent evidence suggests that speakers utilize an acoustic-like reference frame for the planning of speech movements. DIVA, a computational model of speech acquisition and motor equivalent speech production, has previously ...
  • Santini, Fabrizio; Rucci, Michele (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2005-01)
    Many visual cues, both binocular and monocular, provide 3D information. When an agent moves with respect to a scene, an important cue is the different motion of objects located at various distances. While a motion parallax ...
  • Aguilar, J. Mario; Contreras-Vidal, Jose L. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-01)
    An active, attentionally-modulated recognition architecture is proposed for object recognition and scene analysis. The proposed architecture forms part of navigation and trajectory planning modules for mobile robots. Key ...
  • Tan, Can Ozan; Anderson, Eric; Dranias, Mark; Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2007-03)
    Recent electrophysical data inspired the claim that dopaminergic neurons adapt their mismatch sensitivities to reflect variances of expected rewards. This contradicts reward prediction error theory and most basal ganglia ...
  • 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 ...
  • Bullock, Dan; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    This article describes two neural network modules that form part of an emerging theory of how adaptive control of goal-directed sensory-motor skills is achieved by humans and other animals. The Vector-Integration-To-Endpoint ...
  • Fischl, Bruce; Schwartz, Eric (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-11)
    The goal of many early visual filtering processes is to remove noise while at the same time sharpening contrast. An historical succession of approaches to this problem, starting with the use of simple derivative and smoothing ...
  • Fischl, Bruce; Schwartz, Eric L. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, )
    Nonlinear anisotropic diffusion algorithms provide a significant improvement in image enhancement for segmentation, when compared to more traditional linear isotropic filters. However, the excessive computational cost of ...
  • Carpenter, Gail A.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-09-03)
  • 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, ...
  • Tan, Ah-Hwee (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1992-02)
    This paper introduces a new class of predictive ART architectures, called Adaptive Resonance Associative Map (ARAM) which performs rapid, yet stable heteroassociative learning in real time environment. ARAM can be visualized ...
  • Carpenter, Gail A.; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2009-05)
  • Carpenter, Gail; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-09)
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-10)
  • 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 ...
  • Chey, Jonathan (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-05)
    An ndaptive tessellation variant of the CMAC architecture is introduced. Adaptive tessellation is an error-based scheme for distributing input representations. Simulations show that the new network outperforms the original ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-12)
    Examples of how LTP and LTD can control adaptively timed learning that modulates attention and motor control are given. It is also suggested that LTP/LTD can also play a role in storing memories. The distinction between ...
  • 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 ...

Search OpenBU


Advanced Search

Browse

Deposit Materials