Engineering Commons^™

Optimized Learning Using Fuzzy-Inference-Assisted Algorithms For Deep Learning, Miroslava Barua

Open Access Theses & Dissertations

For years, researchers in Artificial Intelligence (AI) and Deep Learning (DL) observed that performance of a Deep Learning Network (DLN) could be improved by using larger and larger datasets coupled with complex network architectures. Although these strategies yield remarkable results, they have limits, dictated by data quantity and quality, rising costs by the increased computational power, or, more frequently, by long training times on networks that are very large. Training DLN requires laborious work involving multiple layers of densely connected neurons, updates to millions of network parameters, while potentially iterating thousands of times through millions of entries in a big …

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 …