[Comp-neuro] Closed-Loop Deep Learning with Robotics, NECO Vol 32, No 11
Sama Daryanavard (PGR)
2089166D at student.gla.ac.uk
Mon Nov 23 22:23:59 CET 2020
In our paper we present Closed-Loop Deep Learning which combines the power of deep learning and classical control to create an efficient analogue multi-layered fast learning paradigm, for robotic navigation. At the heart of this algorithm is an error signal that arises from a reflex which is delicately used to both drive the closed loop system and train the deep learner simultaneously. Through mathematical derivation in z-space we show how to implement back-propagation in a closed-loop system.
Neural Computation (final version):
Please do not hesitate to get in touch for a copy of the paper and to discuss your thoughts.
Dr Bernd Porr
Biomedical Engineering Division, School of Engineering,
University of Glasgow, Glasgow G12 8QQ, U.K.
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the Comp-neuro