The conference focused on alternatives to digital computers for mimicking the cognitive abilities of the human brain.
He explored theorems that could support computing on physical systems other than digital computers.
“My research points toward fundamental mathematical theorems that show how brains and unconventional computing devices have higher processing capability that results from noisy analog signals,” Redd said.
After submitting his abstract for the conference, Redd said he had a “Eureka moment.”
Through his research, he linked together stochastic resonance, when white noise is added to a signal to improve its detection, and a theorem about the processing capabilities of the brain.
“We believe that this is a significant theoretical advance for making neural networks operate more like brain does,” Redd said.
Redd and his Missouri State co-authors described the linkage in a poster for the conference. His co-authors include Dr. A. Steven Younger, physics, astronomy and materials faculty researcher, and Dr. Tayo Obafemi-Ajayi, assistant professor of electrical engineering.
They also submitted an extensive paper to the International Joint Conference on Neural Networks.