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Relevant bibliographies by topics / Binary logic

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Dissertations / Theses

Academic literature on the topic 'Binary logic'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 June 2025

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Dissertations / Theses on the topic "Binary logic"

1

Rönchen, Philipp. "Constraints of Binary Simple Homogeneous Structures." Thesis, Uppsala universitet, Algebra och geometri, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-361217.

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2

Pérez, Manríquez Alejandra. "Quivers for semigroup algebras of binary relations of small rank." Thesis, Uppsala universitet, Algebra och geometri, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-411481.

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3

Heredia, Rico Jobany J. "Simulation and Application of Binary Logic Regression Models." FIU Digital Commons, 2016. http://digitalcommons.fiu.edu/etd/2455.

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Logic regression (LR) is a methodology to identify logic combinations of binary predictors in the form of intersections (and), unions (or) and negations (not) that are linearly associated with an outcome variable. Logic regression uses the predictors as inputs and enables us to identify important logic combinations of independent variables using a computationally efficient tree-based stochastic search algorithm, unlike the classical regression models, which only consider pre-determined conventional interactions (the “and” rules). In the thesis, we focused on LR with a binary outcome in a logistic regression framework. Simulation studies were conducted to examine the performance of LR under the assumption of independent and correlated observations, respectively, for various characteristics of the data sets and LR search parameters. We found that the proportion of times that LR selected the correct logic rule was usually low when the signal and/or prevalence of the true logic rule were relatively low. The method performed satisfactorily under easy learning conditions such as high signal, simple logic rules and/or small numbers of predictors. Given the simulation characteristics and correlation structures tested, we found some but not significant difference in performance when LR was applied to dependent observations compared to the independent case. In addition to simulation studies, an advanced application method was proposed to integrate LR and resampling methods in order to enhance LR performance. The proposed method was illustrated using two simulated data sets as well as a data set from a real-life situation. The proposed method showed some evidence of being effective in discerning the correct logic rule, even for unfavorable learning conditions.

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4

Croson, E., J. Howard, and L. Jue. "Binary Decision Machines: Alternative Logic for Telemetry Control." International Foundation for Telemetering, 1987. http://hdl.handle.net/10150/615292.

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International Telemetering Conference Proceedings / October 26-29, 1987 / Town and Country Hotel, San Diego, California<br>A Binary Decision Machine (BDM) is described as a means of achieving logical control of data acquisition equipment and telemetry systems. The basic architecture of a BDM is initially presented followed by a description of its implementation as a Very Large Scale Integration (VLSI) device. Performance characteristics, programming, and ease of use as a controller are then presented via actual applications. The results of these endeavors led to a means of digitizing and extracting doppler data in a missile telemetry system.

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5

Kelan, Elisabeth Kristina. "Binary logic? : doing gender in information communication technology work." Thesis, London School of Economics and Political Science (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.429370.

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6

Wu, Nicholas(Nicholas T. ). "Inductive logic programming with gradient descent for supervised binary classification." Thesis, Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/129926.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, February, 2020<br>Cataloged from student-submitted PDF of thesis.<br>Includes bibliographical references (pages 75-76).<br>As machine learning techniques have become more advanced, interpretability has become a major concern for models making important decisions. In contrast to Local Interpretable Model-Agnostic Explanations (LIME), this thesis seeks to develop an interpretable model using logical rules, rather than explaining existing blackbox models. We extend recent inductive logic programming methods developed by Evans and Grefenstette [3] to develop an gradient descent-based inductive logic programming technique for supervised binary classification. We start by developing our methodology for binary input data, and then extend the approach to numerical data using a threshold-gate based binarization technique. We test our implementations on datasets with varying pattern structures and noise levels, and select our best performing implementation. We then present an example where our method generates an accurate and interpretable rule set, whereas the LIME technique fails to generate a reasonable model. Further, we test our original methodology on the FICO Home Equity Line of Credit dataset. We run a hyperparameter search over differing number of rules and rule sizes. Our best performing model achieves a 71.7% accuracy, which is comparable to multilayer perceptron and randomized forest models. We conclude by suggesting directions for future applications and potential improvements.<br>by Nicholas Wu.<br>M. Eng.<br>M.Eng. Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science

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7

Shapiro, Albina. "Interface timing verification using constraint logic programming and binary decision diagrams." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=82632.

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The design and verification of high performance circuits is becoming increasingly challenging due to the complex sets of constraints that must hold to ensure correct operation. The complexity of digital circuits increases rapidly, which in turn results in an increased complexity of the verification process and increased user effort. Efficient and easy to use tools are therefore required for timed verification.<br>In this thesis we propose two methods to aid the verification process. Firstly, we introduce a new verification methodology that combines the advantages of several existing successful approaches. In particular, our verification technique uses a combination of untimed, relative timing and timed verification. Secondly, we propose and evaluate a novel method of solving CSPs (constraint satisfaction problems) using BDDs (binary decision diagrams). We investigate two different implementations of a BDD-based CSP solver and their capacity to bridge the gap between untimed and timed verification. Finally, we present two case studies to demonstrate the proposed techniques.

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8

Cartwright, Peter. "Self organising knowledge based control of a binary distillation column." Thesis, Manchester Metropolitan University, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309885.

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9

Jacobi, Ricardo Pezzuol. "A study of the application of binary decision diagrams in multilevel logic synthesis." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1993. http://hdl.handle.net/10183/17646.

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10

Wingfield, James. "Approaches to test set generation using binary decision diagrams." Thesis, Texas A&M University, 2003. http://hdl.handle.net/1969.1/20.

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This research pursues the use of powerful BDD-based functional circuit analysis to evaluate some approaches to test set generation. Functional representations of the circuit allow the measurement of information about faults that is not directly available through circuit simulation methods, such as probability of random detection and test-space overlap between faults. I have created a software tool that performs experiments to make such measurements and augments existing test generation strategies with this new information. Using this tool, I explored the relationship of fault model difficulty to test set length through fortuitous detection, and I experimented with the application of function-based methods to help reconcile the traditionally opposed goals of making test sets that are both smaller and more effective.

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