{"id":"doi:10.1155/2017/1895897","kind":"article","title":"A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots","authors":["Yiming Jiang","Chenguang Yang","Jing Na","Guang Li","Yanan Li","Junpei Zhong"],"author_count":6,"year":2017,"published":"2017-01-01","venue":"Complexity","cited_by":74,"doi":"10.1155/2017/1895897","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1155/2017/1895897","archive_url":"https://space-kitty.com/papers/doi:10.1155/2017/1895897","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W2765544393","pdf_url":"http://downloads.hindawi.com/journals/complexity/2017/1895897.pdf","abstract":"As an imitation of the biological nervous systems, neural networks (NNs), which have been characterized as powerful learning tools, are employed in a wide range of applications, such as control of complex nonlinear systems, optimization, system identification, and patterns recognition. This article aims to bring a brief review of the state-of-the-art NNs for the complex nonlinear systems by summarizing recent progress of NNs in both theory and practical applications. Specifically, this survey also reviews a number of NN based robot control algorithms, including NN based manipulator control, NN based human-robot interaction, and NN based cognitive control.","abstract_license":"CC-BY (publisher license, via OpenAlex)","license":"cc-by","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Neural Networks and Applications"],"details":null,"provenance":"openalex","attribution":"Abstract of \"A Brief Review of Neural Networks Based Learning and Control and Their Applications for Robots\" by Yiming Jiang, Chenguang Yang, Jing Na et al., https://doi.org/10.1155/2017/1895897, used under its Creative Commons Attribution license (CC-BY); markup removed, otherwise unmodified.","topics":[{"slug":"robotics-embodied","name":"Robot Learning & Embodied AI","domain_slug":"ai"}],"cited_in_dossiers":[]}