Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 6 of 6 for “"Entropy (Information theory)"”.
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Investigations into the role of entropy-selected RF-DNA fingerprint features on ID-verification performance in the presence of rogue emitters
… The RF-DNA fingerprints are extracted from the entropy-selected regions within the TF representations of an emitter’s signals. The obtained results demonstrate the success of a Convolutional Neural Network (CNN) in verifying the identities of all authorized emitters at an accuracy rate of 95% or …
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Optimal sensor placement in structural health monitoring (SHM) with a field application on a RC bridge
… optimization approach incorporating information entropy and cost of the sensor network. As the size of the structure grows, the advantage of the optimal sensor network in damage detection becomes obvious. We also present an innovative field application of SHM using Field Programmable …
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On equivalence of additive-combinatorial inequalities for Shannon entropy and differential entropy
Entropy inequalities are very important in information theory and they play a crucial role in various communication-theoretic problems, for example, in the study of the degrees of freedom of interference channels. In this thesis, we are concerned with the additive-combinatorial entropy inequalities …
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Leveraging Information Theory and Ecological Network Analysis to Monitor Communication Networks in a Student Aerospace Team
… the aerospace industry. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to analyze communication networks within a university’s multi-year, student-led cubesat design project (Project COMET). By utilizing Shannon Entropy as a measure of …
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Locally Adaptive Protocols for Quantum State Discrimination
… to two rapidly developing fields: quantum information theory and machine learning. It has recently been demonstrated that reinforcement learning is an effective tool for a wide variety of tasks in quantum information theory, ranging from quantum error correction to quantum control to …
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Landscapes of Finite Information
… principle of statistical inference motivated by information theory. In particular, we argue that if the statistician believes, as we do, that the essence of statistical inference is the compression of data, then the domain of statistical enquiry is fundamentally limited to those probability …