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Journal articles on the topic 'Bidirectional associative memory'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 June 2025

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1

Osana, Yuko, Motonobu Hattori, and Masafumi Hagiwara. "Chaotic Bidirectional Associative Memory." IEEJ Transactions on Electronics, Information and Systems 116, no. 7 (1996): 741–47. http://dx.doi.org/10.1541/ieejeiss1987.116.7_741.

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2

Chen, Songcan, Hang Gao, and Wei Yan. "Improved exponential bidirectional associative memory." Electronics Letters 33, no. 3 (1997): 223. http://dx.doi.org/10.1049/el:19970155.

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3

Tai, H. M., C. H. Wu, and T. L. Jong. "High-order bidirectional associative memory." Electronics Letters 25, no. 21 (1989): 1424. http://dx.doi.org/10.1049/el:19890950.

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4

Yingquan Wu and D. A. Pados. "A feedforward bidirectional associative memory." IEEE Transactions on Neural Networks 11, no. 4 (2000): 859–66. http://dx.doi.org/10.1109/72.857767.

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5

Bělohlávek, Radim. "Fuzzy logical bidirectional associative memory." Information Sciences 128, no. 1-2 (2000): 91–103. http://dx.doi.org/10.1016/s0020-0255(00)00044-x.

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6

Mishchenko, Kirill. "Capacity of bidirectional associative memory." Contemporary Engineering Sciences 8 (2015): 825–33. http://dx.doi.org/10.12988/ces.2015.55160.

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7

Jeng, Y. J., and C. C. Yeh. "Modified intraconnected bidirectional associative memory." Electronics Letters 27, no. 20 (1991): 1818. http://dx.doi.org/10.1049/el:19911129.

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8

Jeng, Y. J., C. C. Yeh, and T. D. Chiueh. "Generalised stable bidirectional associative memory." Electronics Letters 28, no. 15 (1992): 1396. http://dx.doi.org/10.1049/el:19920888.

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9

Baoyun, Wang, Zhang Qing, and He Zhenya. "New exponential bidirectional associative memory." Journal of Electronics (China) 13, no. 1 (1996): 56–60. http://dx.doi.org/10.1007/bf02684715.

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10

Zheng-Ou Wang. "A bidirectional associative memory based on optimal linear associative memory." IEEE Transactions on Computers 45, no. 10 (1996): 1171–79. http://dx.doi.org/10.1109/12.543710.

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11

Eom, Tae-Dok, Changkyu Choi, and Ju-Jang Lee. "Generalized asymmetrical bidirectional associative memory for multiple association." Applied Mathematics and Computation 127, no. 2-3 (2002): 221–33. http://dx.doi.org/10.1016/s0096-3003(00)00170-3.

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12

Hattori, Motonobu, and Masafumi Hagiwara. "Intersection Learning for Bidirectional Associative Memory." IEEJ Transactions on Electronics, Information and Systems 116, no. 7 (1996): 755–61. http://dx.doi.org/10.1541/ieejeiss1987.116.7_755.

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13

Ikeda, Takashi, and Masafumi Hagiwara. "Pruning Algorithms for Bidirectional Associative Memory." IEEJ Transactions on Electronics, Information and Systems 117, no. 3 (1997): 272–78. http://dx.doi.org/10.1541/ieejeiss1987.117.3_272.

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14

Maundy, B., and E. I. El-Masry. "A switched capacitor bidirectional associative memory." IEEE Transactions on Circuits and Systems 37, no. 12 (1990): 1568–72. http://dx.doi.org/10.1109/31.101281.

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15

Zhuang, Xinhua, Yan Huang, and Su-Shing Chen. "Better learning for bidirectional associative memory." Neural Networks 6, no. 8 (1993): 1131–46. http://dx.doi.org/10.1016/s0893-6080(09)80024-5.

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16

Acevedo, María Elena, Cornelio Yáñez-Márquez, and Marco Antonio Acevedo. "Associative Models for Storing and Retrieving Concept Lattices." Mathematical Problems in Engineering 2010 (2010): 1–27. http://dx.doi.org/10.1155/2010/356029.

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Alpha-beta bidirectional associative memories are implemented for storing concept lattices. We use Lindig's algorithm to construct a concept lattice of a particular context; this structure is stored into an associative memory just as a human being does, namely, associating patterns. Bidirectionality and perfect recall of Alpha-Beta associative model make it a great tool to store a concept lattice. In the learning phase, objects and attributes obtained from Lindig's algorithm are associated by Alpha-Beta bidirectional associative memory; in this phase the data is stored. In the recalling phase, the associative model allows to retrieve objects from attributes or vice versa. Our model assures the recalling of every learnt concept.

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17

Rosnita, Lidya, Muhammad Zarlis, and Syahril Efendi. "SISTEM PENDETEKSIAN POLA TAJWID PADA CITRA AL-QUR’AN MENGGUNAKAN ALGORITMA BIDIRECTIONAL ASSOCIATIVE MEMORY." TECHSI - Jurnal Teknik Informatika 8, no. 2 (2019): 91–110. https://doi.org/10.29103/techsi.v8i2.138.

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Pada umumnya didalam dunia pengolahan citra untuk mengenali sebuah pola dapat diberikan beberapa pelatihan terlebih dahulu. Didalam penelitian ini pendeteksian pola tajwid pada citra Al-Qur’an menggunakan empat pola tajwid iqlab, dengan algoritma Bidirectional Associative Memory yang kemudian akan diukur unjuk kerjanya berdasarkan delapan nilai sensitif yang berbeda. Berdasarkan hasil komplesitas algoritma, sistem pendeteksian pola tajwid pada citra Al-Qur’an menggunakan algoritma Bidirectional Associative Memory memiliki kompleksitas sebesar T(n) = (n). Hasil penelitian menunjukkan bahwa sistem pendeteksian pola tajwid pada citra Al-Qur’an menggunakan algoritma Bidirectional Associative Memory memiliki kisaran true detection sebesar 72 % hingga 84 %.

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18

LEUNG, CHI SING, LAI WAN CHAN, and JOHN SUM. "ATTRACTION BASIN OF BIDIRECTIONAL ASSOCIATIVE MEMORIES." International Journal of Neural Systems 07, no. 06 (1996): 715–25. http://dx.doi.org/10.1142/s0129065796000683.

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In this paper, we investigate the attraction basin of the bidirectional associative memory (BAM) model. The BAM is a two-layer heteroassociator that stores a prescribed set of bipolar library pairs. It consists of two layers of neurons. One layer has n neurons and the other has p neurons. We will first point out why the conventional energy approach cannot tell us about the attraction basin of each library pair. We then rigorously derive the statistical dynamics of the BAM, which shows how the upper bound on the number of errors changes during recalling for an arbitrary error pattern in the initial state. From the dynamics, we can estimate the attraction basin for the worst case errors, as well as the memory capacity and the number of errors in the retrieved pairs. The memory capacity is αrn, where αr (0<αr<1) depends on the ratio [Formula: see text]. The number of errors in the retrieved pairs is [Formula: see text] when the number of library pairs is αn. When r=1, the lower bound on the attraction basin for the worst case errors is about 0.0068n.

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19

Wang, Y. F., J. B. Cruz, and J. H. Mulligan. "Two coding strategies for bidirectional associative memory." IEEE Transactions on Neural Networks 1, no. 1 (1990): 81–92. http://dx.doi.org/10.1109/72.80207.

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20

Wang, Y. F., J. B. Cruz, and J. H. Mulligan. "On multiple training for bidirectional associative memory." IEEE Transactions on Neural Networks 1, no. 3 (1990): 275–76. http://dx.doi.org/10.1109/72.80253.

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21

Huang, Gan, and Jinde Cao. "Multistability in bidirectional associative memory neural networks." Physics Letters A 372, no. 16 (2008): 2842–54. http://dx.doi.org/10.1016/j.physleta.2007.12.053.

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22

Zhou, R. W., and C. Quek. "DCBAM: A discrete chainable bidirectional associative memory." Pattern Recognition Letters 17, no. 9 (1996): 985–99. http://dx.doi.org/10.1016/0167-8655(96)00060-8.

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23

Baoyun, Wang, Yang Luxi, and He Zhenya. "A new bidirectional associative memory model—HOMIBAM." Journal of Electronics (China) 12, no. 4 (1995): 325–29. http://dx.doi.org/10.1007/bf02729273.

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24

Lee, Ju-Jang. "Dynamic bidirectional associative memory using chaotic neurons." Artificial Life and Robotics 4, no. 1 (2000): 12–16. http://dx.doi.org/10.1007/bf02481470.

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25

Araújo, Aluizio F. R., Luciana P. P. Bueno, and Marcília A. Campos. "Dynamic behaviors in chaotic bidirectional associative memory." Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology 18, no. 5 (2007): 513–23. https://doi.org/10.3233/ifs-2007-00360.

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26

Masuyama, Naoki, Chu Kiong Loo, and Naoyuki Kubota. "Quantum-Inspired Bidirectional Associative Memory for Human–Robot Communication." International Journal of Humanoid Robotics 11, no. 02 (2014): 1450006. http://dx.doi.org/10.1142/s0219843614500066.

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The emerging research area of a quantum-inspired computing has been applied to various field such as computational intelligence, and showed its superior abilities. However, most existing researches are focused on theoretical simulations, and have not been implemented in systems under practical environment. For human–robot communication, associative memory becomes essential for multi-modal communication. However, it always suffers from low memory capacity and recall reliability. In this paper, we propose a quantum-inspired bidirectional associative memory with fuzzy inference. We show that fuzzy inference satisfies basic postulates of quantum mechanics, but also learning algorithm for weight matrix in associative memory. In addition, we construct a communication system with robot partner using proposed model. This is the first successful attempt to overcome conventional problems in associative memory model with a robot application.

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27

Qadir, Omer, Jerry Liu, Gianluca Tempesti, Jon Timmis, and Andy Tyrrell. "From Bidirectional Associative Memory to a noise-tolerant, robust Protein Processor Associative Memory." Artificial Intelligence 175, no. 2 (2011): 673–93. http://dx.doi.org/10.1016/j.artint.2010.10.008.

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28

Salvadi, Shoba Rani, D. Nagendra Rao, and S. Vathsal. "Optimization of Facial Images to Predict Gender Using HDSON and Bidirectional Associative Memory." Indian Journal Of Science And Technology 16, no. 17 (2023): 1276–83. http://dx.doi.org/10.17485/ijst/v16i17.2481.

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29

Gopalsamy, K., and Xue-Zhong He. "Delay-independent stability in bidirectional associative memory networks." IEEE Transactions on Neural Networks 5, no. 6 (1994): 998–1002. http://dx.doi.org/10.1109/72.329700.

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30

Yen, G. G. "Eigenstructure bidirectional associative memory: an effective synthesis procedure." IEEE Transactions on Neural Networks 6, no. 5 (1995): 1293–97. http://dx.doi.org/10.1109/72.410378.

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31

Zhu, Xiaosheng, and Wei Wu. "Fixed points of complex-valued bidirectional associative memory." Journal of Computational and Applied Mathematics 236, no. 5 (2011): 753–58. http://dx.doi.org/10.1016/j.cam.2011.05.048.

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32

Du, S., Z. Chen, Z. Yuan, and X. Zhang. "Sensitivity to Noise in Bidirectional Associative Memory (BAM)." IEEE Transactions on Neural Networks 16, no. 4 (2005): 887–98. http://dx.doi.org/10.1109/tnn.2005.849832.

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33

Luo, Zhiguo, Jianli Li, and Jianhua Shen. "Stability of Bidirectional Associative Memory networks with impulses." Applied Mathematics and Computation 218, no. 5 (2011): 1658–67. http://dx.doi.org/10.1016/j.amc.2011.06.045.

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34

Liao, Xiaoxin, Yang Liao, and Yu Liao. "Qualitative analysis of bidirectional associative memory neural networks." Journal of Electronics (China) 15, no. 3 (1998): 208–14. http://dx.doi.org/10.1007/s11767-998-0030-y.

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35

Abedin, M. J., and S. I. Ahson. "A new coding procedure for Bidirectional Associative Memory." Journal of Microcomputer Applications 16, no. 2 (1993): 189–95. http://dx.doi.org/10.1006/jmca.1993.1016.

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36

Leung, Chi Sing, and Lai Wan Chan. "The Behavior of Forgetting Learning in Bidirectional Associative Memory." Neural Computation 9, no. 2 (1997): 385–401. http://dx.doi.org/10.1162/neco.1997.9.2.385.

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Forgetting learning is an incremental learning rule in associative memories. With it, the recent learning items can be encoded, and the old learning items will be forgotten. In this article, we analyze the storage behavior of bidirectional associative memory (BAM) under the forgetting learning. That is, “Can the most recent k learning item be stored as a fixed point?” Also, we discuss how to choose the forgetting constant in the forgetting learning such that the BAM can correctly store as many as possible of the most recent learning items. Simulation is provided to verify the theoretical analysis.

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37

Kawaguchi, Satoshi. "Properties of Coupled Oscillator Model for Bidirectional Associative Memory." Journal of the Physical Society of Japan 85, no. 8 (2016): 084001. http://dx.doi.org/10.7566/jpsj.85.084001.

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38

Li, Yingying, Junrui Li, Jie Li, Shukai Duan, Lidan Wang, and Mingjian Guo. "A reconfigurable bidirectional associative memory network with memristor bridge." Neurocomputing 454 (September 2021): 382–91. http://dx.doi.org/10.1016/j.neucom.2021.04.077.

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39

Shen, D., and J. B. Cruz. "Encoding Strategy for Maximum Noise Tolerance Bidirectional Associative Memory." IEEE Transactions on Neural Networks 16, no. 2 (2005): 293–300. http://dx.doi.org/10.1109/tnn.2004.841793.

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40

SHI, GUOYONG. "Genetic approach to the design of bidirectional associative memory." International Journal of Systems Science 28, no. 2 (1997): 133–40. http://dx.doi.org/10.1080/00207729708929371.

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41

Wang, C. C., C. F. Tsai, and J. P. Lee. "Analysis of radix searching of exponential bidirectional associative memory." IEE Proceedings - Computers and Digital Techniques 145, no. 4 (1998): 279. http://dx.doi.org/10.1049/ip-cdt:19982017.

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42

Kumar, S. "Memory annihilation of structured maps in bidirectional associative memories." IEEE Transactions on Neural Networks 11, no. 4 (2000): 1023–30. http://dx.doi.org/10.1109/72.857783.

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43

Tryon, W. "A bidirectional associative memory explanation of posttraumatic stress disorder." Clinical Psychology Review 19, no. 7 (1999): 789–818. http://dx.doi.org/10.1016/s0272-7358(98)00061-0.

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44

Rolon-Merette, Thaddé, Damiem Rolon-Merette, and Sylvain Chartier. "Generating Cognitive Context with Feature-Extracting Bidirectional Associative Memory." Procedia Computer Science 145 (2018): 428–36. http://dx.doi.org/10.1016/j.procs.2018.11.102.

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45

Maeda, Yutaka, and Masatoshi Wakamura. "Bidirectional associative memory with learning capability using simultaneous perturbation." Neurocomputing 69, no. 1-3 (2005): 182–97. http://dx.doi.org/10.1016/j.neucom.2005.02.021.

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46

Srivastava, Vivek, and Vinay Kumar Pathak. "Human Recognition in Passive Environment using Bidirectional Associative Memory." International Journal of Computer Applications 1, no. 15 (2010): 24–26. http://dx.doi.org/10.5120/328-498.

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47

Chartier, Sylvain, Craig Leth-Steensen, and Marie-France Hébert. "Performing complex associations using a generalised bidirectional associative memory." Journal of Experimental & Theoretical Artificial Intelligence 24, no. 1 (2012): 23–42. http://dx.doi.org/10.1080/0952813x.2010.535712.

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48

de los Monteros, Roberto A. Vázquez Espinoza, and Juan Humberto Sossa Azuela. "A Bidirectional Hetero-Associative Memory for True-Color Patterns." Neural Processing Letters 28, no. 3 (2008): 131–53. http://dx.doi.org/10.1007/s11063-008-9086-9.

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49

Chen, Anping, Lihong Huang, Zhigang Liu, and Jinde Cao. "Periodic bidirectional associative memory neural networks with distributed delays." Journal of Mathematical Analysis and Applications 317, no. 1 (2006): 80–102. http://dx.doi.org/10.1016/j.jmaa.2005.09.092.

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50

Du, Sheng-Zhi, Zeng-Qiang Chen, and Zhu-Zhi Yuan. "Evolutionary Pseudo-Relaxation Learning Algorithm for Bidirectional Associative Memory." Journal of Computer Science and Technology 20, no. 4 (2005): 559–66. http://dx.doi.org/10.1007/s11390-005-0559-2.

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