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    A cellular neural network for deformable object modelling

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    Fulltext not available
    Authors
    Zhong, Yongmin
    Shirinzadeh, B.
    Yuan, X.
    Alici, G.
    Smith, J.
    Date
    2006
    Type
    Book Chapter
    
    Metadata
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    Citation
    Zhong, Y. and Shirinzadeh, B. and Yuan, X. and Alici, G. and Smith, J. 2006. A cellular neural network for deformable object modelling, in Shen, W. (ed), Information technology for balanced manufacturing systems. pp. 329-336. Boston: Springer.
    Source Title
    Information Technology For Balanced Manufacturing Systems
    ISBN
    9780387365909
    URI
    http://hdl.handle.net/20.500.11937/32335
    Collection
    • Curtin Research Publications
    Abstract

    This paper presents a new methodology for the deformation of soft objects bydrawing an analogy between cellular neural network (CNN) and elasticdeformation. An improved CNN model is developed to simulate thedeformation of soft objects. A fnite volume based method is presented to derivethe discrete dijferential operators over irregular nets for obtaining the internalelastic forces. The proposed methodology not only models the deformationdynamics in continuum mechanics, but it also simplifies the complexdeformation problem with simple setting CNN templates.

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