Reservoir Computing Optimization: Meeting the Demand for Efficient Network Topologies
TS-065449 — The Need: Modern computational tasks demand efficient and resource-effective solutions. Traditional methods often fall short due to their high resource consumption and power requirements. Reservoir computing, while promising, has faced limitations in optimizing network topologies efficiently, hinder…
- College: College of Arts & Sciences
- Inventors: Griffith, Aaron; Gauthier, Daniel
- Licensing Officer: Dahlman, Jason "Jay"
Deep Reservoir Computers for Precise Chaos Control
TS-065447 — The Need:
In the realm of nonlinear control engineering, managing systems with chaotic dynamics poses a significant challenge. Conventional methods often fall short in achieving precise control over such systems due to their complexity and unpredictability. There's a pressing need for a solutio…
- College: College of Arts & Sciences
- Inventors: Canaday, Daniel; Gauthier, Daniel; Griffith, Aaron
- Licensing Officer: Dahlman, Jason "Jay"
Reservoir Computing: Revolutionizing Rapid Processing
TS-065446 — The Need: In today's fast-paced commercial landscape, there's an increasing demand for rapid processing of complex data sets. Traditional computing methods often struggle to keep pace with real-time requirements, leading to inefficiencies and missed opportunities. Addressing this need for sw…
- College: College of Arts & Sciences
- Inventors: Canaday, Daniel; Gauthier, Daniel; Griffith, Aaron
- Licensing Officer: Dahlman, Jason "Jay"