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Improvement of image processing by using homogeneous neural networks with fractional derivatives theorem
1.  University of Rzeszow, Institute of Technology, 35959 Rzeszow, 16A Rejtana Str. 
[1] 
Ndolane Sene. Fractional input stability and its application to neural network. Discrete & Continuous Dynamical Systems  S, 2020, 13 (3) : 853865. doi: 10.3934/dcdss.2020049 
[2] 
Fangfang Dong, Yunmei Chen. A fractionalorder derivative based variational framework for image denoising. Inverse Problems & Imaging, 2016, 10 (1) : 2750. doi: 10.3934/ipi.2016.10.27 
[3] 
Jianfeng Feng, Mariya Shcherbina, Brunello Tirozzi. Stability of the dynamics of an asymmetric neural network. Communications on Pure & Applied Analysis, 2009, 8 (2) : 655671. doi: 10.3934/cpaa.2009.8.655 
[4] 
Ying Sue Huang, Chai Wah Wu. Stability of cellular neural network with small delays. Conference Publications, 2005, 2005 (Special) : 420426. doi: 10.3934/proc.2005.2005.420 
[5] 
King Hann Lim, Hong Hui Tan, Hendra G. Harno. Approximate greatest descent in neural network optimization. Numerical Algebra, Control & Optimization, 2018, 8 (3) : 327336. doi: 10.3934/naco.2018021 
[6] 
ShyanShiou Chen, ChihWen Shih. Asymptotic behaviors in a transiently chaotic neural network. Discrete & Continuous Dynamical Systems  A, 2004, 10 (3) : 805826. doi: 10.3934/dcds.2004.10.805 
[7] 
Rui Hu, Yuan Yuan. Stability, bifurcation analysis in a neural network model with delay and diffusion. Conference Publications, 2009, 2009 (Special) : 367376. doi: 10.3934/proc.2009.2009.367 
[8] 
HuiQiang Ma, NanJing Huang. Neural network smoothing approximation method for stochastic variational inequality problems. Journal of Industrial & Management Optimization, 2015, 11 (2) : 645660. doi: 10.3934/jimo.2015.11.645 
[9] 
Yixin Guo, Aijun Zhang. Existence and nonexistence of traveling pulses in a lateral inhibition neural network. Discrete & Continuous Dynamical Systems  B, 2016, 21 (6) : 17291755. doi: 10.3934/dcdsb.2016020 
[10] 
Jianhong Wu, Ruyuan Zhang. A simple delayed neural network with large capacity for associative memory. Discrete & Continuous Dynamical Systems  B, 2004, 4 (3) : 851863. doi: 10.3934/dcdsb.2004.4.851 
[11] 
Sanjay K. Mazumdar, ChengChew Lim. A neural network based antiskid brake system. Discrete & Continuous Dynamical Systems  A, 1999, 5 (2) : 321338. doi: 10.3934/dcds.1999.5.321 
[12] 
K. L. Mak, J. G. Peng, Z. B. Xu, K. F. C. Yiu. A novel neural network for associative memory via dynamical systems. Discrete & Continuous Dynamical Systems  B, 2006, 6 (3) : 573590. doi: 10.3934/dcdsb.2006.6.573 
[13] 
Honggang Yu. An efficient face recognition algorithm using the improved convolutional neural network. Discrete & Continuous Dynamical Systems  S, 2019, 12 (4&5) : 901914. doi: 10.3934/dcdss.2019060 
[14] 
Lidong Liu, Fajie Wei, Shenghan Zhou. Major project risk assessment method based on BP neural network. Discrete & Continuous Dynamical Systems  S, 2019, 12 (4&5) : 10531064. doi: 10.3934/dcdss.2019072 
[15] 
Zhuwei Qin, Fuxun Yu, Chenchen Liu, Xiang Chen. How convolutional neural networks see the world  A survey of convolutional neural network visualization methods. Mathematical Foundations of Computing, 2018, 1 (2) : 149180. doi: 10.3934/mfc.2018008 
[16] 
Christina A. Hollon, Jeffrey T. Neugebauer. Positive solutions of a fractional boundary value problem with a fractional derivative boundary condition. Conference Publications, 2015, 2015 (special) : 615620. doi: 10.3934/proc.2015.0615 
[17] 
Ekta Mittal, Sunil Joshi. Note on a $ k $generalised fractional derivative. Discrete & Continuous Dynamical Systems  S, 2020, 13 (3) : 797804. doi: 10.3934/dcdss.2020045 
[18] 
Saif Ullah, Muhammad Altaf Khan, Muhammad Farooq, Zakia Hammouch, Dumitru Baleanu. A fractional model for the dynamics of tuberculosis infection using CaputoFabrizio derivative. Discrete & Continuous Dynamical Systems  S, 2020, 13 (3) : 975993. doi: 10.3934/dcdss.2020057 
[19] 
Saif Ullah, Muhammad Altaf Khan, Muhammad Farooq, Ebraheem O. Alzahrani. A fractional model for the dynamics of tuberculosis (TB) using AtanganaBaleanu derivative. Discrete & Continuous Dynamical Systems  S, 2020, 13 (3) : 937956. doi: 10.3934/dcdss.2020055 
[20] 
Fang Han, Bin Zhen, Ying Du, Yanhong Zheng, Marian Wiercigroch. Global Hopf bifurcation analysis of a sixdimensional FitzHughNagumo neural network with delay by a synchronized scheme. Discrete & Continuous Dynamical Systems  B, 2011, 16 (2) : 457474. doi: 10.3934/dcdsb.2011.16.457 
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