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Richard H. Middleton

Researcher at University of Newcastle

Publications -  396
Citations -  13068

Richard H. Middleton is an academic researcher from University of Newcastle. The author has contributed to research in topics: Control theory & Linear system. The author has an hindex of 48, co-authored 393 publications receiving 12037 citations. Previous affiliations of Richard H. Middleton include Hamilton Institute & University of California.

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Journal ArticleDOI

Energy Efficiency Maximization for Downlink Cloud Radio Access Networks With Data Sharing and Data Compression

TL;DR: Numerical examples with practical parameters confirm that the proposed joint optimization designs markedly improve the C-RAN’s energy efficiency compared to benchmark schemes, and show that the fronthaul data-sharing strategy outperforms its compression-based counterpart in terms of energy efficiency, in both single-hop and multi-hop network scenarios.
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Networked Delay Control for 5G Wireless Machine-Type Communications Using Multiconnectivity

TL;DR: Stability analysis based on integral quadratic constraint theory is applied to characterize the global stability of the controller, and it is stressed that the proposed controller does not require internode time synchronization.
Journal ArticleDOI

Brief Slow stable open-loop poles: to cancel or not to cancel

TL;DR: This paper considers control loops with integral action and shows that shifting slow stable real poles, rather than cancelling them, increases the l"1, H"~, and the point-wise in frequency norms of the complementary sensitivity.
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Dealing with time-varying parameter problem of robot manipulators performing path tracking tasks

TL;DR: Using the properties of the element by element (or Hadamard) product of matrices, this paper obtained the robot dynamics in parameter-isolated form, from which a new control scheme was developed.
Proceedings Article

Application of SVMs for Colour Classification and Collision Detection with AIBO Robots

TL;DR: The method of one-class classification with support vector machines (SVMs) can be applied to solve colour classification and collision detection as they occur in the legged league robot soccer environment of RoboCup satisfactorily using the limited hardware capacity of Sony AIBO quadruped robots.