The RRBF dynamic representation of time in radial basis function network

Zemouri Ryad; Racoceanu Daniel; Zerhouni Noureddine

The RRBF dynamic representation of time in radial basis function network

Zemouri Ryad, Racoceanu Daniel, Zerhouni Noureddine

CNRS Umr 6174

Research output: Contribution to conference › Paper › peer-review

10 Scopus citations

Abstract

This paper introduces the Recurrent Radial Basis Function networks (RRBF) for recognition of simple temporal sequence. The RRBF combines features from recurrent neural network and Radial Basis Function networks (RBF). An application has been developed by implementation on the IBM/ZISC (Zero Instruction Set Computer) card for temporal sequences recognition.

Original language	English
Pages	737-740
Number of pages	4
State	Published - 2001
Externally published	Yes
Event	8th International Conference on Emerging Technologies and Factory Automation (ETFA 2001) - Antibes-Juan les pins, France Duration: 15 Oct 2001 → 18 Oct 2001

Conference

Conference	8th International Conference on Emerging Technologies and Factory Automation (ETFA 2001)
Country/Territory	France
City	Antibes-Juan les pins
Period	15/10/01 → 18/10/01

Cite this

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title = "The RRBF dynamic representation of time in radial basis function network",

abstract = "This paper introduces the Recurrent Radial Basis Function networks (RRBF) for recognition of simple temporal sequence. The RRBF combines features from recurrent neural network and Radial Basis Function networks (RBF). An application has been developed by implementation on the IBM/ZISC (Zero Instruction Set Computer) card for temporal sequences recognition.",

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AU - Daniel, Racoceanu

AU - Noureddine, Zerhouni

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N2 - This paper introduces the Recurrent Radial Basis Function networks (RRBF) for recognition of simple temporal sequence. The RRBF combines features from recurrent neural network and Radial Basis Function networks (RBF). An application has been developed by implementation on the IBM/ZISC (Zero Instruction Set Computer) card for temporal sequences recognition.

AB - This paper introduces the Recurrent Radial Basis Function networks (RRBF) for recognition of simple temporal sequence. The RRBF combines features from recurrent neural network and Radial Basis Function networks (RBF). An application has been developed by implementation on the IBM/ZISC (Zero Instruction Set Computer) card for temporal sequences recognition.

UR - https://www.scopus.com/pages/publications/0035556969

M3 - Paper

AN - SCOPUS:0035556969

SP - 737

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T2 - 8th International Conference on Emerging Technologies and Factory Automation (ETFA 2001)

Y2 - 15 October 2001 through 18 October 2001

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The RRBF dynamic representation of time in radial basis function network

Abstract

Conference

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