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Please use this identifier to cite or link to this item: https://oldena.lpnu.ua/handle/ntb/45233
Title: Analysis of steady-states of continuous-time impulse K-winners-take-all neural network
Authors: Tymoshchuk, Pavlo
Affiliation: Lviv Polytechnic National University
Bibliographic description (Ukraine): Tymoshchuk P. Analysis of steady-states of continuous-time impulse K-winners-take-all neural network / Pavlo Tymoshchuk // САПР у проектуванні машин. Задачі впровадження та навчання : матеріали XXVI Міжнародної українсько-польської науково-технічної конференції, 19-20 жовтня 2018 року, Львів. — Львів : Видавництво Львівської політехніки, 2018. — С. 20–26.
Bibliographic description (International): Tymoshchuk P. Analysis of steady-states of continuous-time impulse K-winners-take-all neural network / Pavlo Tymoshchuk // SAPR u proektuvanni mashyn. Zadachi vprovadzhennia ta navchannia : materialy XXVI Mizhnarodnoi ukrainsko-polskoi naukovo-tekhnichnoi konferentsii, 19-20 zhovtnia 2018 roku, Lviv. — Lviv : Vydavnytstvo Lvivskoi politekhniky, 2018. — P. 20–26.
Is part of: САПР у проектуванні машин. Задачі впровадження та навчання : матеріали XXVI Міжнародної українсько-польської науково-технічної конференції, 2018
Conference/Event: XXVI Міжнародна українсько-польська науково-технічна конференція “САПР у проектуванні машин. Задачі впровадження та навчання”
Journal/Collection: САПР у проектуванні машин. Задачі впровадження та навчання : матеріали XXVI Міжнародної українсько-польської науково-технічної конференції
Issue Date: 19-Oct-2018
Publisher: Видавництво Львівської політехніки
Place of the edition/event: Львів
Temporal Coverage: 19-20 жовтня 2018 року, Львів
Number of pages: 7
Page range: 20-26
Start page: 20
End page: 26
URI: https://ena.lpnu.ua/handle/ntb/45233
ISBN: 978-966-941-229-4
Copyright owner: © Національний університет «Львівська політехніка», 2018
References (Ukraine): [1] E. Majani, R. Erlanson, and Y. Abu-Mostafa, “On the k-winners-take-all network,” in Advances in Neural Information Processing Systems 1, R. P. Lippmann, J. E. Moody, and D. S. Touretzky, Eds. San Mateo, CA: Morgan Kaufmann, 1989, pp. 634-642.
[2] J. Wang, “Analysis and design of a k-winners-take-all network with a single state variable and the Heaviside step activation function,” IEEE Trans. Neural Networks, vol. 21, no. 9, pp. 1496-1506, Sept. 2010.
[3] P. Tymoshchuk, “Stability of impulse K-Winners-Take-All neural network,” Computer Systems of Design. Theory and Practice, No 882,pp. 90-98, 2017.
[4] R. P. Lippmann, “An introduction to computing with neural nets,” IEEE Acoustics, Speech and Signal Processing Magazine, vol. 3, no. 4, pp. 4-22, Apr. 1987.
[5] P.Tymoshchuk and E.Kaszkurewicz, ”A winner-take all circuit using neural networks as building blocks,” Neurocomputing, vol. 64, pp.375-396, Mar. 2005.
[6] X. Cai, D. Prokhorov, and D. Wunsch, “Training winner-take-all simultaneous recurrent neural networks,” IEEE Trans. Neural Networks,vol. 18, no. 3, pp. 674-684, May 2007.
[7] J. Lazzaro, S. Ryckebusch, M. A. Mahowald, and C. A. Mead, “Winnertake- all networks of O(N) complexity,” in Advances in Neural Information Processing Systems 1, R. P. Lippmann, J. E. Moody, and D.S. Touretzky, Eds. San Mateo, CA: Morgan Kaufmann, 1989, pp. 703-711.
[8] B. Sekerkiran and U. Cilingiroglu, “A CMOS K-winners-take-all circuits with 0(N) complexity,” IEEE Trans. Circuits Systems II, vol. 46, no. 1, pp. 1-5, Jan. 1999.
[9] A. Cichocki and R. Unbehauen, Neural Networks for Optimization andSignal Processing. New York, NY, USA: Wiley, 1993.
[10] R. C. O’Reilly and Y. Munakata, Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain. Cambridge, MA: MIT Press, 2000.
[11] W. Maass, “Neural computation with winner-take-all as the only nonlinear operation,” in Advances in Information Processing Systems, vol. 12, S. A. Solla, T. K. Leen, and K.-R. Mueller, Eds. Cambridge, MA: MIT Press, 2000, pp. 293–299.
References (International): [1] E. Majani, R. Erlanson, and Y. Abu-Mostafa, "On the k-winners-take-all network," in Advances in Neural Information Processing Systems 1, R. P. Lippmann, J. E. Moody, and D. S. Touretzky, Eds. San Mateo, CA: Morgan Kaufmann, 1989, pp. 634-642.
[2] J. Wang, "Analysis and design of a k-winners-take-all network with a single state variable and the Heaviside step activation function," IEEE Trans. Neural Networks, vol. 21, no. 9, pp. 1496-1506, Sept. 2010.
[3] P. Tymoshchuk, "Stability of impulse K-Winners-Take-All neural network," Computer Systems of Design. Theory and Practice, No 882,pp. 90-98, 2017.
[4] R. P. Lippmann, "An introduction to computing with neural nets," IEEE Acoustics, Speech and Signal Processing Magazine, vol. 3, no. 4, pp. 4-22, Apr. 1987.
[5] P.Tymoshchuk and E.Kaszkurewicz, "A winner-take all circuit using neural networks as building blocks," Neurocomputing, vol. 64, pp.375-396, Mar. 2005.
[6] X. Cai, D. Prokhorov, and D. Wunsch, "Training winner-take-all simultaneous recurrent neural networks," IEEE Trans. Neural Networks,vol. 18, no. 3, pp. 674-684, May 2007.
[7] J. Lazzaro, S. Ryckebusch, M. A. Mahowald, and C. A. Mead, "Winnertake- all networks of O(N) complexity," in Advances in Neural Information Processing Systems 1, R. P. Lippmann, J. E. Moody, and D.S. Touretzky, Eds. San Mateo, CA: Morgan Kaufmann, 1989, pp. 703-711.
[8] B. Sekerkiran and U. Cilingiroglu, "A CMOS K-winners-take-all circuits with 0(N) complexity," IEEE Trans. Circuits Systems II, vol. 46, no. 1, pp. 1-5, Jan. 1999.
[9] A. Cichocki and R. Unbehauen, Neural Networks for Optimization andSignal Processing. New York, NY, USA: Wiley, 1993.
[10] R. C. O’Reilly and Y. Munakata, Computational Explorations in Cognitive Neuroscience: Understanding the Mind by Simulating the Brain. Cambridge, MA: MIT Press, 2000.
[11] W. Maass, "Neural computation with winner-take-all as the only nonlinear operation," in Advances in Information Processing Systems, vol. 12, S. A. Solla, T. K. Leen, and K.-R. Mueller, Eds. Cambridge, MA: MIT Press, 2000, pp. 293–299.
Content type: Conference Abstract
Appears in Collections:САПР у проектуванні машин. Задачі впровадження та навчання. – 2018 р.

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