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Computer Engineering

University of Texas at El Paso

Theses/Dissertations

Hardware

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Full-Text Articles in Engineering

A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan Jan 2020

A Comprehensive And Modular Robotic Control Framework For Model-Less Control Law Development Using Reinforcement Learning For Soft Robotics, Charles Sullivan

Open Access Theses & Dissertations

Soft robotics is a growing field in robotics research. Heavily inspired by biological systems, these robots are made of softer, non-linear, materials such as elastomers and are actuated using several novel methods, from fluidic actuation channels to shape changing materials such as electro-active polymers. Highly non-linear materials make modeling difficult, and sensors are still an area of active research. These issues have rendered typical control and modeling techniques often inadequate for soft robotics. Reinforcement learning is a branch of machine learning that focuses on model-less control by mapping states to actions that maximize a specific reward signal. Reinforcement learning has …


Investigation Of The Divcon Neuron To Increase The Performance Of A Traditional Feed Forward Multi-Layer Perceptron And Its Hardware Implementation, Jovan Saenz Jan 2012

Investigation Of The Divcon Neuron To Increase The Performance Of A Traditional Feed Forward Multi-Layer Perceptron And Its Hardware Implementation, Jovan Saenz

Open Access Theses & Dissertations

ABSTRACT

Artificial Neural Networks (ANNs) have been developed in an attempt to emulate the information processing capabilities of the biological brain. They offer an alternate computing approach to problems in which mathematical modeling is complicated, such as pattern recognition and pattern classification.

Since ANNs were proposed in the early 1940s, there has been a great amount of research effort dedicated to the development of new models that improve performance. Consequently, different architectures, a variety of activation functions, and distinct learning algorithms have been developed and implemented in different disciplines such as medicine, engineering, and science. In addition, ANNs have been …