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Full-Text Articles in Physical Sciences and Mathematics
Design And Implementation Of A Deterministic And Nondeterministic Finite Automaton Simulator, Camron C. Dennler
Design And Implementation Of A Deterministic And Nondeterministic Finite Automaton Simulator, Camron C. Dennler
Computer Science and Software Engineering
The purpose of this project is to assist students in visualizing and understanding the structure and operation of deterministic and nondeterministic finite automata. This software achieves this purpose by providing students with the ability to build, modify, and test automata in an intuitive environment. This enables a simple and efficient avenue for experimentation, which upholds the Cal Poly ideal of Learning by Doing.
Readers of this report should be familiar with basic concepts in the theory of finite state machines; a general understanding of object-oriented programming is also necessary.
Quantum Random Walk Search And Grover's Algorithm - An Introduction And Neutral-Atom Approach, Anna Maria Houk
Quantum Random Walk Search And Grover's Algorithm - An Introduction And Neutral-Atom Approach, Anna Maria Houk
Physics
In the sub-field of quantum algorithms, physicists and computer scientist take classical computing algorithms and principles and see if there is a more efficient or faster approach implementable on a quantum computer, i.e. a ”quantum advantage”. We take random walks, a widely applicable group of classical algorithms, and move them into the quantum computing paradigm. Additionally, an introduction to a popular quantum search algorithm called Grover’s search is included to guide the reader to the development of a quantum search algorithm using quantum random walks. To close the gap between algorithm and hardware, we will look at using neutral-atom (also …
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Neural Network Pruning For Ecg Arrhythmia Classification, Isaac E. Labarge
Master's Theses
Convolutional Neural Networks (CNNs) are a widely accepted means of solving complex classification and detection problems in imaging and speech. However, problem complexity often leads to considerable increases in computation and parameter storage costs. Many successful attempts have been made in effectively reducing these overheads by pruning and compressing large CNNs with only a slight decline in model accuracy. In this study, two pruning methods are implemented and compared on the CIFAR-10 database and an ECG arrhythmia classification task. Each pruning method employs a pruning phase interleaved with a finetuning phase. It is shown that when performing the scale-factor pruning …