Search Results - "Sagar, B.S.D."

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  1. 1

    Morphological image analysis of transmission systems by Radhakrishnan, P., Sagar, B.S.D., Venkatesh, B.

    Published in IEEE transactions on power delivery (01-01-2005)
    “…This paper proposes morphological decimation of power network images for the purpose of analysis. The method creates a graphical image of a power network with…”
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    Journal Article
  2. 2

    Analysis of geophysical networks derived from multiscale digital elevation models: a morphological approach by Tay, L.T., Sagar, B.S.D., Hean Teik Chuah

    Published in IEEE geoscience and remote sensing letters (01-10-2005)
    “…We provide a simple and elegant framework based on morphological transformations to generate multiscale digital elevation models (DEMs) and to extract…”
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    Journal Article
  3. 3

    Allometric power-law relationships in a Hortonian fractal digital elevation model by Sagar, B. S. Daya, Tien, Tay Lea

    Published in Geophysical research letters (01-03-2004)
    “…We provide a topologically viable model that is geomorphologically realistic from the point of its Hortonity and general allometric scaling laws. To illustrate…”
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    Journal Article
  4. 4

    Allometric relationships between traveltime channel networks, convex hulls, and convexity measures by Tay, L.T, Sagar, B.S.D, Chuah, H.T

    Published in Water resources research (01-06-2006)
    “…The channel network (S) is a nonconvex set, while its basin [C(S)] is convex. We remove open-end points of the channel connectivity network iteratively to…”
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    Journal Article
  5. 5

    A Discriminative Signal Subspace Speech Classifier by Tan, A.W.C., Rao, M.V.C., Sagar, B.S.D.

    Published in IEEE signal processing letters (01-02-2007)
    “…A speech model inspired by the signal subspace methods was recently proposed as a speech classifier with modest results. Fashioned along a "best…”
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    Journal Article
  6. 6

    Convergence index for BPN training by Gunasekaran, S., Venkatesh, B., Sagar, B.S.D.

    Published in Neurocomputing (Amsterdam) (01-10-2003)
    “…The Back Propagation Network (BPN) is one of the most widely used neural networks. It has a distinct training phase and then it is put to use. It is observed…”
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    Journal Article
  7. 7

    Fractal analysis of multiscale pore connectivity networks by Lian, T.L., Sagar, B.S.D.

    “…Mathematical morphology method is applied to extract physically-realistic of pore connectivity network (PCNs) from a sandstone microphotograph. The fractal…”
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    Conference Proceeding