Abstract:
A new technique is presented for designing associative memories to be implemented by Hopfield neural networks. This technique guarantees that each desired memory is store...Show MoreMetadata
Abstract:
A new technique is presented for designing associative memories to be implemented by Hopfield neural networks. This technique guarantees that each desired memory is stored and is attractive. The procedure also guarantees that the resulting network can be implemented, a requirement often overlooked by other methods. This synthetic procedure does not require a symmetric interconnection matrix; instead, stability is guaranteed by use of the results presented by A.N. Michel et al. (1989). Two examples are presented that demonstrate the synthesis procedure's storage ability and flexibility.<>
Published in: IEEE Transactions on Circuits and Systems ( Volume: 37, Issue: 7, July 1990)
DOI: 10.1109/31.55063
Citations are not available for this document.
Cites in Papers - |
Cites in Papers - IEEE (58)
Select All
1.
Garimella Rama Murthy, "Toward Optimal Synthesis of Discrete-Time Hopfield Neural Network", IEEE Transactions on Neural Networks and Learning Systems, vol.34, no.11, pp.9549-9554, 2023.
2.
Fang Liu, Yong He, Yong Li, Mi Dong, "Novel delay-dependent robust stability criteria of hopfield neural networks with time-varying delay", 2017 12th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp.757-761, 2017.
3.
Qian Ma, Gang Feng, Shengyuan Xu, "Delay-Dependent Stability Criteria for Reaction–Diffusion Neural Networks With Time-Varying Delays", IEEE Transactions on Cybernetics, vol.43, no.6, pp.1913-1920, 2013.
4.
Chang-Chun Hua, Xian Yang, Jing Yan, Xin-Ping Guan, "New Exponential Stability Criteria for Neural Networks With Time-Varying Delay", IEEE Transactions on Circuits and Systems II: Express Briefs, vol.58, no.12, pp.931-935, 2011.
5.
Zekeriya Uykan, "A control engineering perspective to radio resource management challenges in emerging cellular/“noncellular” radio systems", 2011 XXIII International Symposium on Information, Communication and Automation Technologies, pp.1-8, 2011.
6.
Li Sheng, Ming Gao, "Robust stability of switched uncertain stochastic recurrent neural networks with discrete and distributed delays", 2011 Chinese Control and Decision Conference (CCDC), pp.3876-3881, 2011.
7.
Xianwei Li, Huijun Gao, Xinghuo Yu, "A Unified Approach to the Stability of Generalized Static Neural Networks With Linear Fractional Uncertainties and Delays", IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol.41, no.5, pp.1275-1286, 2011.
8.
Zhenwei Liu, Huaguang Zhang, Qingling Zhang, "Novel Stability Analysis for Recurrent Neural Networks With Multiple Delays via Line Integral-Type L-K Functional", IEEE Transactions on Neural Networks, vol.21, no.11, pp.1710-1718, 2010.
9.
Liu Yonghua, Luo Wenguang, "Expenential stability of recurrent neural networks with time-varying discrete and distributed delays", 2010 5th International Conference on Computer Science & Education, pp.135-139, 2010.
10.
Huaguang Zhang, Zhenwei Liu, Guang-Bin Huang, Zhanshan Wang, "Novel Weighting-Delay-Based Stability Criteria for Recurrent Neural Networks With Time-Varying Delay", IEEE Transactions on Neural Networks, vol.21, no.1, pp.91-106, 2010.
11.
Rongni Yang, Huijun Gao, Peng Shi, "Novel Robust Stability Criteria for Stochastic Hopfield Neural Networks With Time Delays", IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol.39, no.2, pp.467-474, 2009.
12.
Baoyong Zhang, Shengyuan Xu, Guangdeng Zong, Yun Zou, "Delay-Dependent Exponential Stability for Uncertain Stochastic Hopfield Neural Networks With Time-Varying Delays", IEEE Transactions on Circuits and Systems I: Regular Papers, vol.56, no.6, pp.1241-1247, 2009.
13.
Shaoshuai Mou, Huijun Gao, James Lam, Wenyi Qiang, "A New Criterion of Delay-Dependent Asymptotic Stability for Hopfield Neural Networks With Time Delay", IEEE Transactions on Neural Networks, vol.19, no.3, pp.532-535, 2008.
14.
Shengyuan Xu, Baoyong Zhang, "Delay-Dependent Exponential Stability Analysis for Delayed Stochastic Hopfield Neural Networks", 2007 IEEE International Conference on Control and Automation, pp.448-452, 2007.
15.
Shengyuan Xu, J. Lam, D.W.C. Ho, "A new LMI condition for delay-dependent asymptotic stability of delayed Hopfield neural networks", IEEE Transactions on Circuits and Systems II: Express Briefs, vol.53, no.3, pp.230-234, 2006.
16.
Jinde Cao, Jun Wang, "Global exponential stability and periodicity of recurrent neural networks with time delays", IEEE Transactions on Circuits and Systems I: Regular Papers, vol.52, no.5, pp.920-931, 2005.
17.
Jinde Cao, Jun Wang, "Global asymptotic and robust stability of recurrent neural networks with time delays", IEEE Transactions on Circuits and Systems I: Regular Papers, vol.52, no.2, pp.417-426, 2005.
18.
J. Cao, Jun Wang, "Global asymptotic stability of a general class of recurrent neural networks with time-varying delays", IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, vol.50, no.1, pp.34-44, 2003.
19.
Dongming Zhou, Jianrong Shen, Xiang Ren, "Estimation of attraction domain and exponential convergence rate of dynamic feedback neural nets", WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000, vol.3, pp.1598-1601 vol.3, 2000.
20.
Li Yujian, "Estimate of the number of equilibria in continuous-time Hopfield neural networks", WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000, vol.3, pp.1606-1608 vol.3, 2000.
21.
Jinde Cao, "On the domain of attraction and convergence rate of Hopfield continuous feedback neural networks", Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393), vol.5, pp.3277-3280 vol.5, 2000.
22.
Jinde Cao, Qiong Li, "Estimation of attraction domain and exponential convergence rate of continuous feedback associative memory", Proceedings of the 3rd World Congress on Intelligent Control and Automation (Cat. No.00EX393), vol.2, pp.868-871 vol.2, 2000.
23.
Liang Jin, M.M. Gupta, "Stable dynamic backpropagation learning in recurrent neural networks", IEEE Transactions on Neural Networks, vol.10, no.6, pp.1321-1334, 1999.
24.
Y. Kuroe, K. Koashi, N. Hashimoto, T. Mori, "A learning method for synthesizing associative memory in neural networks", IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), vol.2, pp.798-803 vol.2, 1999.
25.
Li Yujian, "Global stability of Hopfield neural networks", ICSP '98. 1998 Fourth International Conference on Signal Processing (Cat. No.98TH8344), vol.2, pp.1299-1300 vol.2, 1998.
26.
Zheng-Ou Wang, "A bidirectional associative memory based on optimal linear associative memory", IEEE Transactions on Computers, vol.45, no.10, pp.1171-1179, 1996.
27.
Derong Liu, "Feedback neural nets for associative memories-an overview and some new results", Proceedings of the 1996 IEEE International Symposium on Intelligent Control, pp.474-479, 1996.
28.
T. Nakamura, T. Saito, K. Jin'no, "Bifurcation from a hysteresis associative memory", 1996 Fourth IEEE International Workshop on Cellular Neural Networks and their Applications Proceedings (CNNA-96), pp.47-50, 1996.
29.
Zong-Ben Xu, Guo-Qing Hu, Chung-Ping Kwong, "Some efficient strategies for improving the eigenstructure method in synthesis of feedback neural networks", IEEE Transactions on Neural Networks, vol.7, no.1, pp.233-245, 1996.
30.
A. Sperduti, "Stability properties of labeling recursive auto-associative memory", IEEE Transactions on Neural Networks, vol.6, no.6, pp.1452-1460, 1995.
Cites in Papers - Other Publishers (36)
1.
Xifen Wu, Haibo Bao, "H∞ state estimation for multiplex networks with randomly occurring sensor saturations", Applied Mathematics and Computation, vol.437, pp.127538, 2023.
2.
Weiru Guo, Fang Liu, "A new criterion of asymptotic stability for Hopfield neural networks with time-varying delay", iPolytech Journal, vol.25, no.6, pp.753, 2022.
3.
Jianguo Tan, Yahua Tan, Yongfeng Guo, Jianfeng Feng, "Almost sure exponential stability of numerical solutions for stochastic delay Hopfield neural networks with jumps", Physica A: Statistical Mechanics and its Applications, vol.545, pp.123782, 2020.
4.
Yevgeniy Bodyanskiy, Artem Dolotov, Dmytro Peleshko, Yuriy Rashkevych, Olena Vynokurova, "Associative Probabilistic Neuro-Fuzzy System for Data Classification Under Short Training Set Conditions", Contemporary Complex Systems and Their Dependability, vol.761, pp.56, 2019.
5.
K. Subramanian, P. Muthukumar, S. Lakshmanan, "State feedback synchronization control of impulsive neural networks with mixed delays and linear fractional uncertainties", Applied Mathematics and Computation, vol.321, pp.267, 2018.
6.
Zhanshan Wang, Zhenwei Liu, Chengde Zheng, "Survey of Dynamics of Cohen?Grossberg-Type RNNs", Qualitative Analysis and Control of Complex Neural Networks with Delays, vol.34, pp.91, 2016.
7.
Zhanshan Wang, Zhenwei Liu, Chengde Zheng, "Delay-Partitioning-Method Based Stability Results for RNNs", Qualitative Analysis and Control of Complex Neural Networks with Delays, vol.34, pp.173, 2016.
8.
Bo Song, Ya Zhang, Zhan Shu, Fu-Nian Hu, "Stability analysis of Hopfield neural networks perturbed by Poisson noises", Neurocomputing, vol.196, pp.53, 2016.
9.
Guangming Zhuang, Junwei Lu, Minsong Zhang, "Robust H∞ filter design for uncertain stochastic Markovian jump Hopfield neural networks with mode-dependent time-varying delays", Neurocomputing, vol.127, pp.181, 2014.
10.
Wenguang Luo, Xiuling Wang, Yonghua Liu, Hongli Lan, "Novel Global Exponential Stability Criterion for Recurrent Neural Networks with Time-Varying Delay", Abstract and Applied Analysis, vol.2013, pp.1, 2013.
11.
Qingshan Liu, Tingwen Huang, "A neural network with a single recurrent unit for associative memories based on linear optimization", Neurocomputing, vol.118, pp.263, 2013.
12.
Guodong Shi, Qian Ma, Yi Qu, "Robust passivity analysis of a class of discrete-time stochastic neural networks", Neural Computing and Applications, vol.22, no.7-8, pp.1509, 2013.
13.
Zekeriya Uykan, "Discrete Pseudo-SINR-Balancing Nonlinear Recurrent System", Discrete Dynamics in Nature and Society, vol.2013, pp.1, 2013.
14.
Yi-Fu Feng, Qing-Ling Zhang, De-Zhi Feng, "Novel stability criteria for fuzzy Hopfield neural networks based on an improved homogeneous matrix polynomials technique", Chinese Physics B, vol.21, no.10, pp.100701, 2012.
15.
Jun Peng, Zaiming Liu, "pth Moment stability of stochastic neural networks with Markov volatilities", Neural Computing and Applications, vol.20, no.4, pp.543, 2011.
16.
Y. Lu, W. Ren, S. Yi, Y. Zuo, "Stability analysis for discrete delayed Markovian jumping neural networks with partly unknown transition probabilities", Neurocomputing, vol.74, no.18, pp.3768, 2011.
17.
Qian Ma, Shengyuan Xu, Yun Zou, "Stability and synchronization for Markovian jump neural networks with partly unknown transition probabilities", Neurocomputing, vol.74, no.17, pp.3404, 2011.
18.
Qian Ma, Shengyuan Xu, Yun Zou, Jinjun Lu, "Stability of stochastic Markovian jump neural networks with mode-dependent delays", Neurocomputing, vol.74, no.12-13, pp.2157, 2011.
19.
Li Sheng, Ming Gao, Huizhong Yang, "Delay-dependent robust stability for uncertain stochastic fuzzy Hopfield neural networks with time-varying delays", Fuzzy Sets and Systems, vol.160, no.24, pp.3503, 2009.
20.
Guang-Deng Zong, Jia Liu, "New delay-dependent global asymptotic stability condition for Hopfield neural networks with time-varying delays", International Journal of Automation and Computing, vol.6, no.4, pp.415, 2009.
21.
Hongyang Liu, Lin Zhao, Zexu Zhang, Yan Ou, "Stochastic stability of Markovian jumping Hopfield neural networks with constant and distributed delays", Neurocomputing, vol.72, no.16-18, pp.3669, 2009.
22.
He Huang, Daniel W.C. Ho, Yuzhong Qu, "Robust stability of stochastic delayed additive neural networks with Markovian switching", Neural Networks, vol.20, no.7, pp.799, 2007.
23.
Jinde Cao, H.X. Li, Lei Han, "Novel results concerning global robust stability of delayed neural networks", Nonlinear Analysis: Real World Applications, vol.7, no.3, pp.458, 2006.
24.
Jinde Cao, Daniel W.C. Ho, "A general framework for global asymptotic stability analysis of delayed neural networks based on LMI approach", Chaos, Solitons & Fractals, vol.24, no.5, pp.1317, 2005.
25.
He Huang, Yuzhong Qu, Han-Xiong Li, "Robust stability analysis of switched Hopfield neural networks with time-varying delay under uncertainty", Physics Letters A, vol.345, no.4-6, pp.345, 2005.
26.
He Huang, Jinde Cao, Yuzhong Qu, "Global robust stability of delayed neural networks with a class of general activation functions", Journal of Computer and System Sciences, vol.69, no.4, pp.688, 2004.
27.
Jinde Cao, "An estimation of the domain of attraction and convergence rate for Hopfield continuous feedback neural networks", Physics Letters A, vol.325, no.5-6, pp.370, 2004.
28.
Jinde Cao, Qing Tao, "Estimation on Domain of Attraction and Convergence Rate of Hopfield Continuous Feedback Neural Networks", Journal of Computer and System Sciences, vol.62, no.3, pp.528, 2001.
29.
Jinde Cao, Qing Tao, "Estimation of the Domain of Attraction and the Convergence Rate of a Hopfield Associative Memory and an Application", Journal of Computer and System Sciences, vol.60, no.1, pp.179, 2000.
30.
Miao Zhenjiang, Yuan Baozong, "Analysis and optimal design of continuous neural networks with applications to associative memory", Neural Networks, vol.12, no.2, pp.259, 1999.
