{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,4]],"date-time":"2025-12-04T14:33:41Z","timestamp":1764858821095,"version":"3.41.0"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319181639"},{"type":"electronic","value":"9783319181646"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-18164-6_35","type":"book-chapter","created":{"date-parts":[[2015,6,5]],"date-time":"2015-06-05T08:55:38Z","timestamp":1433494538000},"page":"359-368","source":"Crossref","is-referenced-by-count":7,"title":["On the Use of Quantum-inspired Optimization Techniques for Training Spiking Neural Networks: A New Method Proposed"],"prefix":"10.1007","author":[{"given":"Maurizio","family":"Fiasch\u00e9","sequence":"first","affiliation":[]},{"given":"Marco","family":"Taisch","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"35_CR1","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.tins.2004.10.010","volume":"28","author":"R. VanRullen","year":"2005","unstructured":"VanRullen, R., Guyonneau, R., Thorpe, S.: Spike times make sense. Trends Neurosci.\u00a028, 1\u20134 (2005)","journal-title":"Trends Neurosci."},{"key":"35_CR2","doi-asserted-by":"publisher","first-page":"1659","DOI":"10.1016\/S0893-6080(97)00011-7","volume":"10","author":"W. Maass","year":"1997","unstructured":"Maass, W.: Networks of spiking neurons: The third generation of neural network models. Neural Networks\u00a010, 1659\u20131671 (1997)","journal-title":"Neural Networks"},{"key":"35_CR3","doi-asserted-by":"crossref","unstructured":"Wysoski, S.G., Benuskova, L., Kasabov, N.: On-line learning with structural adaptation in a network of spiking neurons for visual pattern recognition. ICANN\u00a0(1), 61\u201370 (2006)","DOI":"10.1007\/11840817_7"},{"key":"35_CR4","series-title":"SCI","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/978-3-642-04025-2_3","volume-title":"Brain-Inspired Information Technology","author":"S.G. Wysoski","year":"2010","unstructured":"Wysoski, S.G., Benuskova, L., Kasabov, N.: Brain-like evolving spiking neural networks for multimodal information processing. In: Hanazawa, A., Miki, T., Horio, K. (eds.) Brain-Inspired Information Technology. SCI, vol.\u00a0266, pp. 15\u201327. Springer, Heidelberg (2010)"},{"issue":"1-4","key":"35_CR5","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/S0925-2312(01)00658-0","volume":"48","author":"S.M. Bohte","year":"2002","unstructured":"Bohte, S.M., Kok, J.N., Poutre, H.L.: Error-Backpropagation in Temporally Encoded Networks of Spiking Neurons. Neurocomputing\u00a048(1-4), 17\u201337 (2002)","journal-title":"Neurocomputing"},{"key":"35_CR6","volume-title":"Evolving Connectionist Systems: The System Engineering Approach","author":"N. Kasabov","year":"2007","unstructured":"Kasabov, N.: Evolving Connectionist Systems: The System Engineering Approach, vol.\u00a02. Springer-Verlag New York Inc., Secaucus (2007)"},{"key":"35_CR7","unstructured":"Thorpe, S.J.: How Can the Human Visual System Process a Natural Scene in Under 150ms? Experiments and Neural Network Models. In: Verleysen, M. (ed.) Proceedings of European Symposium on Artificial Neural Networks, D-Facto public, ISBN 2-9600049-7-3, Bruges, Belgium (1997)"},{"key":"35_CR8","doi-asserted-by":"crossref","unstructured":"Soltic, S., Wysoski, S., Kasabov, N.: Evolving spiking neural networks for taste recognition. In: IEEE World Congress on Computational Intelligence (WCCI), Hong Kong (2008)","DOI":"10.1109\/IJCNN.2008.4634085"},{"key":"35_CR9","doi-asserted-by":"crossref","unstructured":"Defoin-Platel, M., Schliebs, S., Kasabov, N.: A versatile quantum-inspired evolutionary algorithm. In: IEEE Congress on Evolutionary Computation, CEC 2007, pp. 423\u2013430 (2007)","DOI":"10.1109\/CEC.2007.4424502"},{"key":"35_CR10","doi-asserted-by":"publisher","first-page":"623","DOI":"10.1016\/j.neunet.2009.06.038","volume":"22","author":"S. Schliebs","year":"2009","unstructured":"Schliebs, S., Defoin-Platel, M., Worner, S., Kasabov, N.: Integrated Feature and Parameter Optimization for an Evolving Spiking Neural Network: Exploring Heterogeneous Probabilistic Models. Neural Networks\u00a022, 623\u2013632 (2009)","journal-title":"Neural Networks"},{"issue":"6","key":"35_CR11","doi-asserted-by":"publisher","first-page":"1218","DOI":"10.1109\/TEVC.2008.2003010","volume":"13","author":"M.D. Platel","year":"2009","unstructured":"Platel, M.D., Schliebs, S., Kasabov, N.: Quantum-Inspired Evolutionary Algorithm: A Multimodel EDA. IEEE Transactions on Evolutionary Computation\u00a013(6), 1218\u20131232 (2009)","journal-title":"IEEE Transactions on Evolutionary Computation"},{"key":"35_CR12","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1007\/978-3-642-34487-9_83","volume-title":"Neural Information Processing","author":"M. Fiasch\u00e9","year":"2012","unstructured":"Fiasch\u00e9, M.: A Quantum-Inspired Evolutionary Algorithm for Optimization Numerical Problems. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds.) ICONIP 2012, Part III. LNCS, vol.\u00a07665, pp. 686\u2013693. Springer, Heidelberg (2012)"},{"key":"35_CR13","doi-asserted-by":"crossref","unstructured":"Han, K.H., Kim, J.H.: Quantum-inspired evolutionary algorithm for a class of combinatorial optimization. IEEE Transactions on Evolutionary Computation, 580\u2013593 (2002)","DOI":"10.1109\/TEVC.2002.804320"},{"key":"35_CR14","doi-asserted-by":"crossref","unstructured":"Eberhart, R., Kennedy, J.: A new optimizer using particle swarm theory. In: Proc. Sixth International Symposium on Micro Machine and Human Science, pp. 39\u201343. IEEE Press (1995)","DOI":"10.1109\/MHS.1995.494215"},{"key":"35_CR15","unstructured":"Sun, J., Feng, B., Xu, W.B.: Particle swarm optimization with particles having quantum behavior. In: Proc. Congress on Evolutionary Computation, vol.\u00a01, pp. 325\u2013331 (2004)"},{"key":"35_CR16","doi-asserted-by":"crossref","unstructured":"Hamed, H.N.A., Kasabov, N., Shamsuddin, S.M.: Integrated feature selection and parameter optimization for evolving spiking neural networks using quantum inspired particle swarm optimization. In: Soft Computing and Pattern Recognition, SoCPaR 2009, pp. 695\u2013698 (2009)","DOI":"10.1109\/SoCPaR.2009.139"},{"key":"35_CR17","doi-asserted-by":"crossref","unstructured":"Hamed, H.N.A., Kasabov, N., Shamsuddin, S.M.: Quantum-Inspired Particle Swarm Optimization for Feature Selection and Parameter Optimization in Evolving Spiking Neural Networks for Classification Tasks. In: Kita, E. (ed.) Evolutionary Algorithms, InTech (2011)","DOI":"10.7763\/IJMO.2012.V2.108"},{"issue":"2","key":"35_CR18","doi-asserted-by":"publisher","first-page":"189","DOI":"10.1109\/TNN.2008.2005601","volume":"20","author":"P. Estavest","year":"2009","unstructured":"Estavest, P., Tesmer, M., Perez, C., Zurada, J.: Normalized mutual information feature selection. Neural Networks\u00a020(2), 189\u2013201 (2009)","journal-title":"Neural Networks"},{"key":"35_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1007\/978-3-642-02490-0_1","volume-title":"Advances in Neuro-Information Processing","author":"N. Kasabov","year":"2009","unstructured":"Kasabov, N.: Integrative probabilistic evolving spiking neural networks utilising quantum inspired evolutionary algorithm: A computational framework. In: K\u00f6ppen, M., Kasabov, N., Coghill, G. (eds.) ICONIP 2008, Part I. LNCS, vol.\u00a05506, pp. 3\u201313. Springer, Heidelberg (2009)"},{"key":"35_CR20","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1016\/j.neunet.2014.01.006","volume":"52","author":"N.K. Kasabov","year":"2014","unstructured":"Kasabov, N.K.: NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data. Neural Networks\u00a052, 62\u201376 (2014)","journal-title":"Neural Networks"}],"container-title":["Smart Innovation, Systems and Technologies","Advances in Neural Networks: Computational and Theoretical Issues"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-18164-6_35","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T10:38:57Z","timestamp":1748428737000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-18164-6_35"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319181639","9783319181646"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-18164-6_35","relation":{},"ISSN":["2190-3018","2190-3026"],"issn-type":[{"type":"print","value":"2190-3018"},{"type":"electronic","value":"2190-3026"}],"subject":[],"published":{"date-parts":[[2015]]}}}