A Convolution Universal Generating Function Method For Evaluating The Symbolic One-To-All-Target-Subset Reliability Function Of Acyclic Multi-State Information Networks

Yeh, W

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Publication date

January 2009

DOI

10.1109/TR.2009.2026688

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

ISSN

0018-9529

Journal

IEEE Transactions on Reliability

Abstract

The acyclic multi-state information network (AMIN) is an extension of the multi-state network without having to satisfy the flow conservation law. A very straightforward convolution universal generating function method (CUGFM) is developed to find the e

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A Convolution Universal Generating Function Method For Evaluating The Symbolic One-To-All-Target-Subset Reliability Function Of Acyclic Multi-State Information Networks

Abstract

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A Convolution Universal Generating Function Method For Evaluating The Symbolic One-To-All-Target-Subset Reliability Function Of Acyclic Multi-State Information Networks

Abstract

Extracted data

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