Search Results - "Eilbert, J."

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  1. 1

    3D atlases - bridges between neurogenomics and neuroanatomy by Nissanov, J., Eilbert, J., Tretiak, O.J., Gefen, S., Schremmer, S., Gustafson, C., Bertrand, L.

    “…Neuroscience research in the post-genomic era requires rapid screening and analysis of large tissue expanse. It demands close integration of information…”
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    Conference Proceeding
  2. 2

    Axon shape as a basis for multinode functional units in a hierarchical neural model by Eilbert, J L

    Published in Journal of theoretical biology (07-01-1988)
    “…The ability of animals to perform fixed action patterns and to access information by categories suggests that there are several types of hierarchical…”
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    Journal Article
  3. 3

    The variation in user drawn outlines on digital images: effects on quantitative autoradiography by Eilbert, J L, Gallistel, C R, McEachron, D L

    Published in Computerized medical imaging and graphics (01-09-1990)
    “…Variation in user outlines drawn to delineate neural regions is the only source of error added to autoradiographic images after the images have been digitized…”
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    Journal Article
  4. 4

    The analytic and functional accuracy of a video densitometry system by McEachron, D L, Gallistel, C R, Eilbert, J L, Tretiak, O J

    Published in Journal of neuroscience methods (01-08-1988)
    “…Applications using radiotracers and quantitative film autoradiography are increasing dramatically in the neurosciences. Microcomputer-based image analyzing…”
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    Journal Article
  5. 5

    Neural-network-based nonlinear inverse flight control by Huang, C., Tylock, J., Engel, S., Whitson, J., Eilbert, J.

    “…The use of neural networks (NNs) as an integral part of nonlinear dynamic inverse flight control is examined. The approach is to train the NNs to carry out the…”
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    Conference Proceeding
  6. 6

    Prediction and Metacognition by Eilbert, J L

    “…A case is made for the following claims. Higher animals have evolved the ability to make predictions because it increases their chance of survival. The basic…”
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    Conference Proceeding
  7. 7

    Computational-complexity reduction for neural network algorithms by Guez, A., Kam, M., Eilbert, J.L.

    “…An important class of neural models is described as a set of coupled nonlinear differential equations with state variables corresponding to the axon hillock…”
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    Journal Article
  8. 8

    Neural network architecture for control by Guez, A., Eilbert, J.L., Kam, M.

    Published in IEEE Control Systems Magazine (01-04-1988)
    “…Two important computational features of neural networks are associative storage and retrieval of knowledge, and uniform rate of convergence of network dynamics…”
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    Journal Article
  9. 9
  10. 10

    Neuromorphic architectures for fast adaptive robot control by Guez, A., Eilbert, J., Kam, M.

    “…An architecture for an adaptive neuromorphic system designed to control a robot is suggested. The proposed architecture utilizes two important features of…”
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    Conference Proceeding