Decision Trees For Fault Diagnosis In Circuits And Switching Networks


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Decision Trees for Fault Diagnosis in Circuits and Switching Networks


Decision Trees for Fault Diagnosis in Circuits and Switching Networks

Author: Monther Busbait

language: en

Publisher: Springer Nature

Release Date: 2023-08-10


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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.

Entropy Measures for Data Analysis


Entropy Measures for Data Analysis

Author: Karsten Keller

language: en

Publisher: MDPI

Release Date: 2019-12-19


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Entropies and entropy-like quantities play an increasing role in modern non-linear data analysis. Fields that benefit from this application range from biosignal analysis to econophysics and engineering. This issue is a collection of papers touching on different aspects of entropy measures in data analysis, as well as theoretical and computational analyses. The relevant topics include the difficulty to achieve adequate application of entropy measures and the acceptable parameter choices for those entropy measures, entropy-based coupling, and similarity analysis, along with the utilization of entropy measures as features in automatic learning and classification. Various real data applications are given.

Advances in Guidance, Navigation and Control


Advances in Guidance, Navigation and Control

Author: Liang Yan

language: en

Publisher: Springer Nature

Release Date: 2021-11-12


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This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircraft. It covers a range of topics, including, but not limited to, intelligent computing communication and control; new methods of navigation, estimation, and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation, and control of miniature aircraft; and sensor systems for guidance, navigation, and control. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.