Abstract
This thesis presents a dynamical system approach to learning forward and inverse models in associative recurrent neural networks. Ambiguous inverse models are represented by multi-stable dynamics. Random projection networks, i.e. reservoirs, together with a rigorous regularization methodology enable robust and efficient training of multi-stable dynamics with application to movement control in robotics.
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Reinhart, R.F. Reservoir Computing with Output Feedback. Künstl Intell 26, 415–416 (2012). https://doi.org/10.1007/s13218-012-0187-2
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DOI: https://doi.org/10.1007/s13218-012-0187-2