Zijiang Yang

Dr. Zijiang Yang

York University, Toronto, Ontario, Canada
orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 July 2006 in Expert Systems with Applications
Verified
Journal Article
Closed access
DWDesheng Wu
Desheng Wu
ZYZijiang Yang
Zijiang Yang
LLLiang Liang
Liang Liang

1 April 2006 in Mathematical and Computer Modelling
Verified
Journal Article
Closed access
ZYZijiang Yang
Zijiang Yang

1 July 2011 in Expert Systems with Applications
Verified
Journal Article
Closed access
ZYZijiang Yang
Zijiang Yang
WYWenjie You
Wenjie You
GJGuoli Ji
Guoli Ji

2 June 2009 in IEEE Transactions on Neural Networks
Verified
Journal Article
Closed access
YXYonghui Xia
Yonghui Xia
ZYZijiang Yang
Zijiang Yang
MHMaoan Han
Maoan Han
This paper considers the lag synchronization (LS) issue of unknown coupled chaotic delayed Yang-Yang-type fuzzy neural networks (YYFCNN) with noise perturbation. Separate research work has been published on the stability of fuzzy neural network and LS issue of unknown coupled chaotic neural networks, as well as its application in secure communication. However, there have not been any studies that integrate the two. Motivated by the achievements from both fields, we explored the benefits of integrating fuzzy logic theories into the study of LS problems and applied the findings to secure communication. Based on adaptive feedback control techniques and suitable parameter identification, several sufficient conditions are developed to guarantee the LS of coupled chaotic delayed YYFCNN with or without noise perturbation. The problem studied in this paper is more general in many aspects. Various problems studied extensively in the literature can be treated as special cases of the findings of this paper, such as complete synchronization (CS), effect of fuzzy logic, and noise perturbation. This paper presents an illustrative example and uses simulated results of this example to show the feasibility and effectiveness of the proposed adaptive scheme. This research also demonstrates the effectiveness of application of the proposed adaptive feedback scheme in secure communication by comparing chaotic masking with fuzziness with some previous studies. Chaotic signal with fuzziness is more complex, which makes unmasking more difficult due to the added fuzzy logic.

1 May 2006 in Computers & Operations Research
Verified
Journal Article
Closed access
MMManuel Muñiz
Manuel Muñiz
JPJoseph Paradi
Joseph Paradi
JRJohn Ruggiero
John Ruggiero
ZYZijiang Yang
Zijiang Yang

1 September 2009 in Communications in Nonlinear Science and Numerical Simulation
Verified
Journal Article
Closed access
YXYonghui Xia
Yonghui Xia
ZYZijiang Yang
Zijiang Yang
MHMaoan Han
Maoan Han