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Institution

Northeastern University (China)

EducationShenyang, China
About: Northeastern University (China) is a education organization based out in Shenyang, China. It is known for research contribution in the topics: Control theory & Microstructure. The organization has 36087 authors who have published 36125 publications receiving 426807 citations. The organization is also known as: Dōngběi Dàxué & Northeastern University (东北大学).


Papers
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Journal ArticleDOI
TL;DR: The linear matrix inequality (LMI) method is applied to propose some new sufficient stability conditions for the reaction-diffusion Cohen-Grossberg neural networks with continuously distributed delays to improve upon the existing stability results.
Abstract: This paper is concerned with the global asymptotic stability of a class of reaction-diffusion Cohen-Grossberg neural networks with continuously distributed delays. Under some suitable assumptions and using a matrix decomposition method, we apply the linear matrix inequality (LMI) method to propose some new sufficient stability conditions for the reaction-diffusion Cohen-Grossberg neural networks with continuously distributed delays. The obtained results are easy to check and improve upon the existing stability results. Some remarks are given to show the advantages of the obtained results over the previous results. An example is also given to demonstrate the effectiveness of the obtained results.

133 citations

Journal ArticleDOI
TL;DR: This paper presents a novel adaptive fuzzy backstepping dynamic surface control scheme for a class of single-input single-output strict-feedback fractional-order uncertain nonlinear systems, which contain unknown nonlinear functions and unknown external disturbances.
Abstract: This paper presents a novel adaptive fuzzy backstepping dynamic surface control (DSC) scheme for a class of single-input single-output strict-feedback fractional-order uncertain nonlinear systems. The controlled systems contain unknown nonlinear functions and unknown external disturbances. Fuzzy logic systems are employed for approximating the unknown nonlinear functions. Further, an auxiliary function is introduced into the control function to simultaneously compensate the unknown external disturbance and the approximation error caused by fuzzy approximation, which erases the possible chattering phenomenon in the existing results. Meanwhile, a new DSC method based on the fractional-order filter is proposed to avoid the issue of explosion of complexity inherent in the backstepping procedure, which releases the limitation that the fractional-order derivative of the intermediate control function needs to be completly known in the existing references. Under certain assumptions, the stability of the closed-loop system is proved by using the fractional-order Lyapunov function stability criterion. Finally, contrastive simulation results are provided to validate the effectiveness of our proposed control strategy.

133 citations

Journal ArticleDOI
TL;DR: In this paper, a thermoelectric material consisting of Cu2Se incorporated with up to 045% of graphene nanoplates is reported, which exhibits an ultra-high thermoclectric figure-of-merit.

132 citations

Journal ArticleDOI
TL;DR: Based on the characteristic of magnetic-controlling refractive index, the magnetic fluid filled in hollow-core photonic crystal fiber (HC-PCF) can be used as the sensitive medium in the cavity of a fiber Fabry-Perot (F-P) magnetic field sensor.
Abstract: Based on the characteristic of magnetic-controlling refractive index, the magnetic fluid filled in hollow-core photonic crystal fiber (HC-PCF) can be used as the sensitive medium in the cavity of a fiber Fabry–Perot (F–P) magnetic field sensor. The structure and the sensor principle are introduced. The theoretical simulations of the mode distribution of the HC-PCF filled with the magnetic fluid and the sensor output spectra are discussed in detail. The sensor multiplexing capability is indicated as well. Magnetic field measurement sensitivity is about 33 pm/Oe based on the proposed sensor.

132 citations

Journal ArticleDOI
10 May 2018
TL;DR: This paper provides a summary of IoT security attacks and develops a taxonomy and classification based on the application domain and underlying system architecture and discusses some key characteristics of IoT that make it difficult to develop robust security architectures for IoT applications.
Abstract: Recent years have seen rapid development and deployment of Internet-of-Things (IoT) applications in a diversity of application domains. This has resulted in creation of new applications (e.g., vehicle networking, smart grid, and wearables) as well as advancement, consolidation, and transformation of various traditional domains (e.g., medical and automotive). One upshot of this scale and diversity of applications is the emergence of new and critical threats to security and privacy: it is getting increasingly easier for an adversary to break into an application, make it unusable, or steal sensitive information and data. This paper provides a summary of IoT security attacks and develops a taxonomy and classification based on the application domain and underlying system architecture. We also discuss some key characteristics of IoT that make it difficult to develop robust security architectures for IoT applications.

132 citations


Authors

Showing all 36436 results

NameH-indexPapersCitations
Rui Zhang1512625107917
Hui-Ming Cheng147880111921
Yonggang Huang13679769290
Yang Liu1292506122380
Tao Zhang123277283866
J. R. Dahn12083266025
Terence G. Langdon117115861603
Frank L. Lewis114104560497
Xin Li114277871389
Peng Wang108167254529
David J. Hill107136457746
Jian Zhang107306469715
Xuemin Shen106122144959
Yi Zhang102181753417
Tao Li102248360947
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023166
2022906
20214,689
20204,118
20193,653
20182,878