Editorial Biologically Learned/Inspired Methods for Sensing, Control, and Decision

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Abstract

The Special Issue aims at collecting new ideas and contributions at the frontier of bridging the gap between biological and engineering systems. Contributions include a wide range of related research topics, from neural computing to adaptive control and cooperative control, from autonomous decision systems to mathematical and computational models, and from neuropsychology-based decision and control to engineering system sensing and control algorithms, as well as applications and case studies of biologically inspired systems. This editorial note provides a brief overview of the accepted articles.

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Song, Y., Si, J., Coleman, S., & Kerr, D. (2022, May 1). Editorial Biologically Learned/Inspired Methods for Sensing, Control, and Decision. IEEE Transactions on Neural Networks and Learning Systems. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/TNNLS.2022.3161003

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