Search Results - "Neville, R.S"

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  1. 1

    Applying Evolutionary Computing to Complex Systems Design by Sutcliffe, A., Wei-Chung Chang, Neville, R.S.

    “…Development of an evolutionary computing tool for requirements analysis and optimization of component-based systems is described. The tool assesses scenarios…”
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    Journal Article
  2. 2

    Transformations of sigma–pi nets: obtaining reflected functions by reflecting weight matrices by Neville, R.S., Eldridge, S.

    Published in Neural networks (01-04-2002)
    “…This paper presents a methodology that reflected functions by reflecting the weight matrices of an artificial neural network. One of the major problems with…”
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    Journal Article
  3. 3

    Performing basic mathematics with neurons/nets. I by Neville, R.S.

    “…We introduce a way of performing basic mathematics or symbolic algebra with neurons. The method is novel because we enable knowledge encapsulated in trained…”
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    Conference Proceeding
  4. 4

    Performing mathematics with neurons or neural networks trained to represent non-linear functions. II by Neville, R.S.

    “…For part I see IEEE WCCI-2002 World Congress Computational Intelligence. The article introduces a way of performing mathematics with neurons trained to map…”
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    Conference Proceeding
  5. 5

    Partially pre-calculated weights for the backpropagation learning regime and high accuracy function mapping using continuous input RAM-based sigma–pi nets by Neville, R.S., Stonham, T.J., Glover, R.J.

    Published in Neural networks (2000)
    “…In this article we present a methodology that partially pre-calculates the weight updates of the backpropagation learning regime and obtains high accuracy…”
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    Journal Article
  6. 6

    Learning Boolean functions without training by Luk, P.C.K., Neville, R.S.

    “…This paper presents a new theory that enables one to obtain a set of Boolean functions from one learnt Boolean function. We do this by transposition of the…”
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    Conference Proceeding
  7. 7

    Toward second-order generalisation by Neville, R.S., Luk, P.C.K.

    “…Generalisation in artificial neural networks may be cast into two basic categories, 'standard' and 'higher-order'. We view 'standard' generalisation as a means…”
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    Conference Proceeding
  8. 8

    Introduction to adaptive weight lattice neural networks by Neville, R.S., Luk, P.C.K.

    “…Research into RAM-based neural networks has now been in progress for approximately two decades. In this paper we introduce a novel way to visualise RAM-based…”
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    Conference Proceeding
  9. 9

    Inheritance of information in multi-layer sigma-pi neural networks by Neville, R.S.

    “…This article shows that prior knowledge may be incorporated into a neural network by using the knowledge in a trained net to prescribe the weights for a new…”
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    Conference Proceeding
  10. 10

    Third-order generalization and a new approach to systematically categorizing higher-order generalization by Neville, R.S.

    “…Higher-order generalization is a means of categorizing different types of generalization. The paper presents a framework within which higher-order…”
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    Conference Proceeding
  11. 11

    Information reuse and integration in artificial neural networks by Neville, R.S.

    “…The need to reuse information is urgent, and a shift is required in the development (understanding - research) of methodologies, with a more reuse-centric view…”
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    Conference Proceeding
  12. 12

    Second-order generalization by Neville, R.S.

    “…Second-order generalization is usually of a more abstract nature than standard generalization, as unseen stimuli may be classified by some higher order rule…”
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    Conference Proceeding
  13. 13

    RAM-based Sigma-pi nets for high accuracy function mapping by Neville, R.S

    “…We investigate the use of digital "Higher Order" Sigma-pi nodes and study continuous input RAM-based Sigma-pi units trained with the backpropagation training…”
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    Conference Proceeding
  14. 14

    Evaluation of training and mapping Sigma-pi networks to a massively parallel processor by Neville, R.S., Glover, R.J., Stonham, T.J.

    “…This paper presents a methodology for training and mapping Sigma-pi networks on to a massively parallel processing (MPP) system. The implementation uses a…”
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    Conference Proceeding