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Decision trees for fault diagnosis in circuits and switching networks

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Decision trees for fault diagnosis in circuits and switching networks/ by Monther Busbait ... [et al.].
other author:	Busbait, Monther.
Published:	Cham :Springer Nature Switzerland : : 2023.,
Description:	xii, 130 p. :ill., digital ; : 24 cm.;
Contained By:	Springer Nature eBook
Subject:	Electric fault location. -
Online resource:	https://doi.org/10.1007/978-3-031-39031-9
ISBN:	9783031390319

Decision trees for fault diagnosis in circuits and switching networks
Decision trees for fault diagnosis in circuits and switching networks[electronic resource] /by Monther Busbait ... [et al.]. - Cham :Springer Nature Switzerland :2023. - xii, 130 p. :ill., digital ;24 cm. - Studies in systems, decision and control,v. 4932198-4190 ;. - Studies in systems, decision and control ;v. 2. .

Introduction -- Diagnosis of constant Faults at Inputs of Gates in Circuits -- Diagnosis of Embedding Faults in Circuits -- Diagnosis of Extensions of Constant Faults in Circuits -- Diagnosis of Retaining Faults in Circuits -- Diagnosis of Constant Faults in Switching Networks.

In this book, we study decision trees for fault diagnosis in circuits and switching networks, which are among the most fundamental models for computing Boolean functions. We consider two main cases: when the scheme (circuit or switching network) has the same mode of operation for both calculation and diagnostics, and when the scheme has two modes of operation-normal for calculation and special for diagnostics. In the former case, we get mostly negative results, including superpolynomial lower bounds on the minimum depth of diagnostic decision trees depending on scheme complexity and the NP-hardness of construction diagnostic decision trees. In the latter case, we describe classes of schemes and types of faults for which decision trees can be effectively used to diagnose schemes, when they are transformed into so-called iteration-free schemes. The tools and results discussed in this book help to understand both the possibilities and challenges of using decision trees to diagnose faults in various schemes. The book is useful to specialists both in the field of theoretical and technical diagnostics. It can also be used for the creation of courses for graduate students.

ISBN: 9783031390319

Standard No.: 10.1007/978-3-031-39031-9doiSubjects--Topical Terms:

1024958
Electric fault location.

LC Class. No.: TK3226

Dewey Class. No.: 620.00452

Decision trees for fault diagnosis in circuits and switching networks
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505 0 $a Introduction -- Diagnosis of constant Faults at Inputs of Gates in Circuits -- Diagnosis of Embedding Faults in Circuits -- Diagnosis of Extensions of Constant Faults in Circuits -- Diagnosis of Retaining Faults in Circuits -- Diagnosis of Constant Faults in Switching Networks.
520 $a In this book, we study decision trees for fault diagnosis in circuits and switching networks, which are among the most fundamental models for computing Boolean functions. We consider two main cases: when the scheme (circuit or switching network) has the same mode of operation for both calculation and diagnostics, and when the scheme has two modes of operation-normal for calculation and special for diagnostics. In the former case, we get mostly negative results, including superpolynomial lower bounds on the minimum depth of diagnostic decision trees depending on scheme complexity and the NP-hardness of construction diagnostic decision trees. In the latter case, we describe classes of schemes and types of faults for which decision trees can be effectively used to diagnose schemes, when they are transformed into so-called iteration-free schemes. The tools and results discussed in this book help to understand both the possibilities and challenges of using decision trees to diagnose faults in various schemes. The book is useful to specialists both in the field of theoretical and technical diagnostics. It can also be used for the creation of courses for graduate students.
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