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Articles 121 - 124 of 124
Full-Text Articles in Theory and Algorithms
Efficient Randomized Algorithms For The Fixed Precision Low Rank Matrix Approximation, Wenjian Yu, Yu Gu, Yaohang Li
Efficient Randomized Algorithms For The Fixed Precision Low Rank Matrix Approximation, Wenjian Yu, Yu Gu, Yaohang Li
Computer Science Faculty Publications
Randomized algorithms for low-rank matrix approximation are investigated, with the emphasis on the fixed-precision problem and computational efficiency for handling large matrices. The algorithms are based on the so-called QB factorization, where Q is an orthonormal matrix. First, a mechanism for calculating the approximation error in the Frobenius norm is proposed, which enables efficient adaptive rank determination for a large and/or sparse matrix. It can be combined with any QB-form factorization algorithm in which B's rows are incrementally generated. Based on the blocked randQB algorithm by Martinsson and Voronin, this results in an algorithm called randQB_EI. Then, we further revise …
Dynamic Output Feedback Invariants Of Full Relative Degree Nonlinear Siso Systems, W. Steven Gray, Luis A. Duffaut Espinosa
Dynamic Output Feedback Invariants Of Full Relative Degree Nonlinear Siso Systems, W. Steven Gray, Luis A. Duffaut Espinosa
Electrical & Computer Engineering Faculty Publications
The goal of this paper is to explicitly describe invariants of a plant described by a Chen--Fliess series under a class of dynamic output feedback laws using earlier work by the authors on feedback transformation groups. The main result requires the rather strong assumption that the plant has a generating series with both finite Lie rank and full relative degree. In which case, there is no loss of generality in working with state space realizations of the plant. An additional genericness assumption regarding the normal form of the plant is also required, but as shown by the examples, this condition …
Applying Machine Learning To Advance Cyber Security: Network Based Intrusion Detection Systems, Hassan Hadi Latheeth Al-Maksousy
Applying Machine Learning To Advance Cyber Security: Network Based Intrusion Detection Systems, Hassan Hadi Latheeth Al-Maksousy
Computer Science Theses & Dissertations
Many new devices, such as phones and tablets as well as traditional computer systems, rely on wireless connections to the Internet and are susceptible to attacks. Two important types of attacks are the use of malware and exploiting Internet protocol vulnerabilities in devices and network systems. These attacks form a threat on many levels and therefore any approach to dealing with these nefarious attacks will take several methods to counter. In this research, we utilize machine learning to detect and classify malware, visualize, detect and classify worms, as well as detect deauthentication attacks, a form of Denial of Service (DoS). …
Logic -> Proof -> Rest, Maxwell Taylor
Logic -> Proof -> Rest, Maxwell Taylor
Senior Independent Study Theses
REST is a common architecture for networked applications. Applications that adhere to the REST constraints enjoy significant scaling advantages over other architectures. But REST is not a panacea for the task of building correct software. Algebraic models of computation, particularly CSP, prove useful to describe the composition of applications using REST. CSP enables us to describe and verify the behavior of RESTful systems. The descriptions of each component can be used independently to verify that a system behaves as expected. This thesis demonstrates and develops CSP methodology to verify the behavior of RESTful applications.