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Citation(s) in
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For:
Li J
, Zhou W, Yang Z.
State estimation and input-to-state stability of impulsive stochastic BAM neural networks with mixed delays.
Neurocomputing
2017. [DOI:
10.1016/j.neucom.2016.08.101
]
[
Citation(s) in
RCA
: 11
]
[
Impact Index Per Article: 1.6
]
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Reference Citation Analysis
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[Indexed: 12/01/2022]
Number
Cited by Other Article(s)
1
Chandrasekar A
, Radhika T, Zhu Q. Further Results on Input-to-State Stability of Stochastic Cohen–Grossberg BAM Neural Networks with Probabilistic Time-Varying Delays.
Neural Process Lett
2021. [DOI:
10.1007/s11063-021-10649-w
]
[
Citation(s) in
RCA
: 0
]
[
Impact Index Per Article: 0
]
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[Indexed: 10/20/2022]
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2
Global dynamics and learning algorithm of non-autonomous neural networks with time-varying delays.
Neurocomputing
2020. [DOI:
10.1016/j.neucom.2019.03.093
]
[
Citation(s) in
RCA
: 2
]
[
Impact Index Per Article: 0.5
]
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[Indexed: 11/21/2022]
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3
Fu Q
, Cai J, Zhong S, Yu Y, Shan Y. Input-to-state stability of discrete-time memristive neural networks with two delay components.
Neurocomputing
2019. [DOI:
10.1016/j.neucom.2018.10.017
]
[
Citation(s) in
RCA
: 4
]
[
Impact Index Per Article: 0.8
]
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[Indexed: 10/28/2022]
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4
Exponential input-to-state stability for complex-valued memristor-based BAM neural networks with multiple time-varying delays.
Neurocomputing
2018. [DOI:
10.1016/j.neucom.2017.10.038
]
[
Citation(s) in
RCA
: 33
]
[
Impact Index Per Article: 5.5
]
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[Indexed: 11/22/2022]
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