A Modified Learning Algorithm for Interval Perceptrons with Interval Weights

In many applications, it is natural to use interval data to describe various kinds of uncertainties. This paper is concerned with a one-layer interval perceptron with the weights and the outputs being intervals and the inputs being real numbers. In the original learning method for this interval perc...

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Veröffentlicht in:	Neural processing letters 2015-10, Vol.42 (2), p.381-396
Hauptverfasser:	Yang, Dakun, Li, Zhengxue, Liu, Yan, Zhang, Huisheng, Wu, Wei
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence Back propagation Complex Systems Computational Intelligence Computer Science Convergence Error functions Intervals Machine learning Neural networks Pattern recognition Real numbers Regression analysis Smoothness Teaching methods
Online-Zugang:	Volltext
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