ZISC Neural Network Base Indicator for Classification Complexity Estimation

Ivan Budnyk, Abdennasser Сhebira, Kurosh Madani

Abstract

This paper presents a new approach for estimating task complexity using IBM© Zero Instruction Set Computer (ZISC ©). The goal is to build a neural tree structure following the paradigm “divide and rule”. The aim of this work is to define a complexity indicator-function and to hallmark its’ main features.

References

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Paper Citation


in Harvard Style

Budnyk I., Сhebira A. and Madani K. (2007). ZISC Neural Network Base Indicator for Classification Complexity Estimation . In Proceedings of the 3rd International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2007) ISBN 978-972-8865-86-3, pages 38-47. DOI: 10.5220/0001635600380047


in Bibtex Style

@conference{anniip07,
author={Ivan Budnyk and Abdennasser Сhebira and Kurosh Madani},
title={ZISC Neural Network Base Indicator for Classification Complexity Estimation},
booktitle={Proceedings of the 3rd International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2007)},
year={2007},
pages={38-47},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001635600380047},
isbn={978-972-8865-86-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 3rd International Workshop on Artificial Neural Networks and Intelligent Information Processing - Volume 1: ANNIIP, (ICINCO 2007)
TI - ZISC Neural Network Base Indicator for Classification Complexity Estimation
SN - 978-972-8865-86-3
AU - Budnyk I.
AU - Сhebira A.
AU - Madani K.
PY - 2007
SP - 38
EP - 47
DO - 10.5220/0001635600380047