派博傳思國(guó)際中心

標(biāo)題: Titlebook: Dynamical Behaviors of Fractional-Order Complex Dynamical Networks; Jin-Liang Wang Book 2024 The Editor(s) (if applicable) and The Author( [打印本頁(yè)]

作者: 文化修養(yǎng)    時(shí)間: 2025-3-21 18:38
書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks影響因子(影響力)




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks被引頻次




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks被引頻次學(xué)科排名




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks年度引用




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks年度引用學(xué)科排名




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks讀者反饋




書(shū)目名稱(chēng)Dynamical Behaviors of Fractional-Order Complex Dynamical Networks讀者反饋學(xué)科排名





作者: legitimate    時(shí)間: 2025-3-21 21:55

作者: 仔細(xì)檢查    時(shí)間: 2025-3-22 03:22

作者: 詳細(xì)目錄    時(shí)間: 2025-3-22 05:24
,Synchronization and?Adaptive Control for?Coupled Fractional-Order Reaction-Diffusion Neural Networkce fractional-order neural networks (FONNs) can more effectively and accurately describe human brain neurons, plenty of work has been devoted to the dynamical behavior for FONNs [.,.,.,.,.,.]. The stability for fractional-order delayed Hopfield NNs was addressed in [.], and the cases that the networ
作者: 易受刺激    時(shí)間: 2025-3-22 09:36

作者: Abrupt    時(shí)間: 2025-3-22 15:41
Passivity of Coupled Fractional-Order Neural Networks with Multiple State and Derivative Couplings,have been extensively explored, which is not only beneficial to better understand the dynamical characteristics of the NNs but also to make better use of these dynamical behaviors in many fields such as model identification, parallel computation and combinatorial optimization.
作者: Abrupt    時(shí)間: 2025-3-22 18:56

作者: maladorit    時(shí)間: 2025-3-22 22:36

作者: 挑剔為人    時(shí)間: 2025-3-23 03:55

作者: 郊外    時(shí)間: 2025-3-23 07:58
,Passivity for?Multiadaptive Coupled Fractional-Order Reaction-Diffusion Neural Networks,rently depend on the stability of NNs. Therefore, a large number of stability results for all kinds of NNs have been given in recent years [.,.,.,.,.,.,.,.]. Li et al. [.] introduced a state-dependent switched fuzzy NN including discrete delay and distributed delay, and developed several exponential
作者: finite    時(shí)間: 2025-3-23 13:19
,Synchronization and?Adaptive Control for?Coupled Fractional-Order Reaction-Diffusion Neural Network. In [.], several exponential stability conditions were presented for a type of complex-valued memristive recurrent NNs by using the .-matrix. By artfully constructing Lyapunov functionals based on delay-product type functionals, two delay-dependent sufficient conditions for stability of NNs were pr
作者: Tracheotomy    時(shí)間: 2025-3-23 15:42
https://doi.org/10.1007/978-981-97-2950-0Fractional-order; complex dynamical networks; coupled neural networks; multiple derivative couplings; mu
作者: 漫不經(jīng)心    時(shí)間: 2025-3-23 22:07
978-981-97-2952-4The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
作者: Measured    時(shí)間: 2025-3-24 00:08
Jin-Liang WangProvides a comprehensive overview of the dynamical behaviors for fractional-order complex networks.Illustrates the relationship between the synchronization and passivity for fractional-order complex n
作者: Tailor    時(shí)間: 2025-3-24 03:48
http://image.papertrans.cn/e/image/283823.jpg
作者: 有權(quán)    時(shí)間: 2025-3-24 09:53
Passivity of Coupled Fractional-Order Neural Networks with Multiple State and Derivative Couplings,have been extensively explored, which is not only beneficial to better understand the dynamical characteristics of the NNs but also to make better use of these dynamical behaviors in many fields such as model identification, parallel computation and combinatorial optimization.
作者: 擁護(hù)者    時(shí)間: 2025-3-24 11:36

作者: antipsychotic    時(shí)間: 2025-3-24 15:16

作者: 乏味    時(shí)間: 2025-3-24 22:09
https://doi.org/10.1007/978-3-642-72986-7hors focus on the dynamical behaviors of fractional-order neural networks (FONNs) in recent years [.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.,.]. Specially, in view of the fact that passivity can effectively handle stabilization and stability, much attention has been paid to the passivity for FONNs [.,.,.,.,
作者: Entirety    時(shí)間: 2025-3-25 03:15

作者: 驚呼    時(shí)間: 2025-3-25 06:20
Biomass conversion in South Africa,mical behaviors for numerous real systems such as urban subway networks, intercity population flow networks, public traffic roads networks and so forth. Up to now, various dynamical behaviors (e.g., synchronization, passivity, stability and so on) for many different kinds of CNs have been fully expl
作者: Omnipotent    時(shí)間: 2025-3-25 11:20
https://doi.org/10.1007/978-3-476-05008-3rently depend on the stability of NNs. Therefore, a large number of stability results for all kinds of NNs have been given in recent years [.,.,.,.,.,.,.,.]. Li et al. [.] introduced a state-dependent switched fuzzy NN including discrete delay and distributed delay, and developed several exponential
作者: MUMP    時(shí)間: 2025-3-25 14:07

作者: declamation    時(shí)間: 2025-3-25 19:31
have been extensively explored, which is not only beneficial to better understand the dynamical characteristics of the NNs but also to make better use of these dynamical behaviors in many fields such as model identification, parallel computation and combinatorial optimization.
作者: 致敬    時(shí)間: 2025-3-25 23:24

作者: Ingrained    時(shí)間: 2025-3-26 03:14

作者: 挫敗    時(shí)間: 2025-3-26 05:13
https://doi.org/10.1007/978-1-84628-995-8n to the dynamical behaviors (such as passivity [., .], synchronization [.,.,.,.,.] and stability [.]) for CDNs, which is not only useful to have a better understanding of many natural phenomena but also beneficial to better take advantage of these dynamical behaviors.
作者: cataract    時(shí)間: 2025-3-26 10:59

作者: incredulity    時(shí)間: 2025-3-26 14:31

作者: gruelling    時(shí)間: 2025-3-26 17:32

作者: 怪物    時(shí)間: 2025-3-26 23:14
ronization, etc.) for fractional-order complex networks (FOCNs) have attracted considerable research attention in a wide range of fields, and a variety of valuable results have been reported. In particular, passivity has been extensively used to address the synchronization of FOCNs.?.978-981-97-2952-4978-981-97-2950-0
作者: 施加    時(shí)間: 2025-3-27 01:31
Passivity and Finite-Time Passivity for Multi-Weighted Fractional-Order Complex Networks with Fixedn to the dynamical behaviors (such as passivity [., .], synchronization [.,.,.,.,.] and stability [.]) for CDNs, which is not only useful to have a better understanding of many natural phenomena but also beneficial to better take advantage of these dynamical behaviors.
作者: craving    時(shí)間: 2025-3-27 08:48

作者: mitral-valve    時(shí)間: 2025-3-27 10:38

作者: 緊張過(guò)度    時(shí)間: 2025-3-27 14:01

作者: 磨坊    時(shí)間: 2025-3-27 21:11

作者: scrape    時(shí)間: 2025-3-28 01:30
https://doi.org/10.1007/978-3-642-72986-7rion for a delayed FONN by leveraging the Razumikhin fractional-order theorem, and derived a sufficient condition to guarantee the passivity for such network on the basis of the presented stability criterion.
作者: Promotion    時(shí)間: 2025-3-28 03:35
Finite-Time Passivity for Coupled Fractional-Order Neural Networks with Multistate or Multiderivatirion for a delayed FONN by leveraging the Razumikhin fractional-order theorem, and derived a sufficient condition to guarantee the passivity for such network on the basis of the presented stability criterion.
作者: 學(xué)術(shù)討論會(huì)    時(shí)間: 2025-3-28 07:48
10樓
作者: LARK    時(shí)間: 2025-3-28 10:52
10樓




歡迎光臨 派博傳思國(guó)際中心 (http://www.pjsxioz.cn/) Powered by Discuz! X3.5
理塘县| 临颍县| 河北区| 锡林郭勒盟| 札达县| 玉门市| 广东省| 那曲县| 林州市| 新丰县| 横山县| 浑源县| 穆棱市| 广丰县| 鄂托克前旗| 乐安县| 五大连池市| 罗田县| 荃湾区| 永宁县| 青河县| 化州市| 许昌市| 和龙市| 涪陵区| 理塘县| 堆龙德庆县| 新昌县| 黄龙县| 阿勒泰市| 崇仁县| 包头市| 安龙县| 乌鲁木齐县| 苍梧县| 庐江县| 乌拉特中旗| 错那县| 鄂伦春自治旗| 南乐县| 永登县|