Southeast University

About: Southeast University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & MIMO. The organization has 66363 authors who have published 79434 publications receiving 1170576 citations. The organization is also known as: SEU.

Planar Ultrawideband Antennas With Multiple Notched Bands Based on Etched Slots on the Patch and/or Split Ring Resonators on the Feed Line

Abstract: Three types of ultrawideband (UWB) antennas with triple notched bands are proposed and investigated for UWB communication applications. The proposed antennas consist of a planar circular patch monopole UWB antenna and multiple etched slots on the patch and/or split ring resonators (SRRs) coupled to the feed line. Good agreement is achieved between the simulated and measured results. These techniques are significant for designing UWB antennas with multiple narrow frequency notched bands or for designing multiband antennas.

Nonlinear-Disturbance-Observer-Based Robust Flight Control for Airbreathing Hypersonic Vehicles

Abstract: The work presented here is concerned with the robust flight control problem for the longitudinal dynamics of a generic airbreathing hypersonic vehicles (AHVs) under mismatched disturbances via a nonlinear-disturbance-observer-based control (NDOBC) method. Compared with other robust flight control method for AHV, the proposed method obtains not only promising robustness and disturbance rejection performance but also the property of nominal performance recovery. The merits of the proposed method are validated by simulation studies.

Global exponential stability and periodicity of recurrent neural networks with time delays

Abstract: In this paper, the global exponential stability and periodicity of a class of recurrent neural networks with time delays are addressed by using Lyapunov functional method and inequality techniques. The delayed neural network includes the well-known Hopfield neural networks, cellular neural networks, and bidirectional associative memory networks as its special cases. New criteria are found to ascertain the global exponential stability and periodicity of the recurrent neural networks with time delays, and are also shown to be different from and improve upon existing ones.