Grienggrai Rajchakit

Prof. Grienggrai Rajchakit

Maejo university
orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

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

Representative Publications

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19 August 2019 in Mathematics
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Journal Article
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GRGrienggrai Rajchakit
Grienggrai Rajchakit
PAPratap Anbalagan
Pratap Anbalagan
RRRaja Ramachandran
Raja Ramachandran
Jinde CaoJinde Cao
Jinde Cao
Jehad AlzabutJehad Alzabut
Jehad Alzabut
CHChuangxia Huang
Chuangxia Huang
This sequel is concerned with the analysis of projective lag synchronization of Riemann–Liouville sense fractional order memristive BAM neural networks (FOMBNNs) with mixed time delays via hybrid controller. Firstly, a new type of hybrid control scheme, which is the combination of open loop control and adaptive state feedback control is designed to guarantee the global projective lag synchronization of the addressed FOMBNNs model. Secondly, by using a Lyapunov–Krasovskii functional and Barbalet’s lemma, a new brand of sufficient criterion is proposed to ensure the projective lag synchronization of the FOMBNNs model considered. Moreover, as special cases by using a hybrid control scheme, some sufficient conditions are derived to ensure the global projective synchronization, global complete synchronization and global anti-synchronization for the FOMBNNs model considered. Finally, numerical simulations are provided to check the accuracy and validity of our obtained synchronization results.

4 January 2021 in Neural Processing Letters
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GRGrienggrai Rajchakit
Grienggrai Rajchakit
RSR. Sriraman
R. Sriraman

14 March 2020 in Mathematics
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Journal Article
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GRGrienggrai Rajchakit
Grienggrai Rajchakit
PCPharunyou Chanthorn
Pharunyou Chanthorn
PKPramet Kaewmesri
Pramet Kaewmesri
RSRamalingam Sriraman
Ramalingam Sriraman
Chee Peng LimChee Peng Lim
Chee Peng Lim
This paper studies the global Mittag–Leffler stability and stabilization analysis of fractional-order quaternion-valued memristive neural networks (FOQVMNNs). The state feedback stabilizing control law is designed in order to stabilize the considered problem. Based on the non-commutativity of quaternion multiplication, the original fractional-order quaternion-valued systems is divided into four fractional-order real-valued systems. By using the method of Lyapunov fractional-order derivative, fractional-order differential inclusions, set-valued maps, several global Mittag–Leffler stability and stabilization conditions of considered FOQVMNNs are established. Two numerical examples are provided to illustrate the usefulness of our analytical results.

19 November 2019 in Neural Processing Letters
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Journal Article
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PAPratap Anbalagan
Pratap Anbalagan
RRR. Raja
R. Raja
JAJ. Alzabut
J. Alzabut
Joseph DianavinnarasiJoseph Dianavinnarasi
Joseph Dianavinnarasi
Jinde CaoJinde Cao
Jinde Cao
GRGrienggrai Rajchakit
Grienggrai Rajchakit

1 March 2019 in Journal of the Franklin Institute
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Journal Article
Closed access
PAPratap Anbalagan
Pratap Anbalagan
RRR. Raja
R. Raja
Jinde CaoJinde Cao
Jinde Cao
GRGrienggrai Rajchakit
Grienggrai Rajchakit
Habib FardounHabib Fardoun
Habib Fardoun

5 March 2024 in Information Sciences
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Journal Article
Closed access
MKMourad Kchaou
Mourad Kchaou
MTM. Mubeen Tajudeen
M. Mubeen Tajudeen
MAM. Syed Ali
M. Syed Ali
GRGrienggrai Rajchakit
Grienggrai Rajchakit
GSG. Shanthi
G. Shanthi
Jinde CaoJinde Cao
Jinde Cao