Journal article
A trainable neuromorphic controller
Journal of robotic systems, Vol.5(4), pp.363-388
01 Aug 1988
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Neuromorphic architecture is employed in the design of Trainable Adaptive Controllers (TACs). A neurocontroller is designed for controlling a nonlinear dynamic system. Various training models are employed: linear, nonlinear,'human' and 'filtered human'. It is found that the computational features of neural networks offer useful capabilities, such as fast, real time, and robust performance when employed as trainable adaptive controllers. (Author)
Metrics
3 Record Views
Details
- Title
- A trainable neuromorphic controller
- Creators
- Allon GuezJohn Selinsky
- Publication Details
- Journal of robotic systems, Vol.5(4), pp.363-388
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Electrical and Computer Engineering
- Identifiers
- 991019183928904721
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Web of Science research areas
- Robotics