{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T03:21:08Z","timestamp":1740108068492,"version":"3.37.3"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"18","license":[{"start":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T00:00:00Z","timestamp":1568332800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T00:00:00Z","timestamp":1568332800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100004543","name":"China Scholarship Council","doi-asserted-by":"crossref","award":["201606630032"],"award-info":[{"award-number":["201606630032"]}],"id":[{"id":"10.13039\/501100004543","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1007\/s00521-019-04479-0","type":"journal-article","created":{"date-parts":[[2019,9,13]],"date-time":"2019-09-13T20:04:46Z","timestamp":1568405086000},"page":"14247-14261","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A new intelligent pattern classifier based on deep-thinking"],"prefix":"10.1007","volume":"32","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5612-4043","authenticated-orcid":false,"given":"Zhenyi","family":"Shen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhihong","family":"Man","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenwei","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinchuan","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,9,13]]},"reference":[{"key":"4479_CR1","first-page":"65","volume":"5","author":"SVH Solari","year":"2011","unstructured":"Solari SVH, Stoner RM (2011) Cognitive consilience: primate non-primary neuroanatomical circuits underlying cognition. Front Neuroanat 5:65","journal-title":"Front Neuroanat"},{"key":"4479_CR2","unstructured":"LeCun Y et al (1990) Handwritten digit recognition with a back-propagation network. In: Advances in neural information processing systems, 1990, pp 396\u2013404"},{"issue":"3","key":"4479_CR3","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1023\/A:1018628609742","volume":"9","author":"JA Suykens","year":"1999","unstructured":"Suykens JA, Vandewalle J (1999) Least squares support vector machine classifiers. Neural Process Lett 9(3):293\u2013300","journal-title":"Neural Process Lett"},{"key":"4479_CR4","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.neunet.2014.10.001","volume":"61","author":"G Huang","year":"2015","unstructured":"Huang G, Huang G-B, Song S, You K (2015) Trends in extreme learning machines: a review. Neural Netw 61:32\u201348","journal-title":"Neural Netw"},{"issue":"1","key":"4479_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1186\/2251-712X-9-1","volume":"9","author":"STA Niaki","year":"2013","unstructured":"Niaki STA, Hoseinzade S (2013) Forecasting S&P 500 index using artificial neural networks and design of experiments. J Ind Eng Int 9(1):1","journal-title":"J Ind Eng Int"},{"key":"4479_CR6","doi-asserted-by":"crossref","unstructured":"Scherer D, M\u00fcller A, Behnke S (2010) Evaluation of pooling operations in convolutional architectures for object recognition. In: International conference on artificial neural networks, 2010. Springer, pp 92\u2013101","DOI":"10.1007\/978-3-642-15825-4_10"},{"key":"4479_CR7","unstructured":"Yosinski J, Clune J, Nguyen A, Fuchs T, Lipson H (2015) Understanding neural networks through deep visualization. arXiv preprint \narXiv:1506.06579"},{"issue":"6","key":"4479_CR8","doi-asserted-by":"publisher","first-page":"1624","DOI":"10.1016\/j.sigpro.2012.07.016","volume":"93","author":"Z Man","year":"2013","unstructured":"Man Z, Lee K, Wang D, Cao Z, Khoo S (2013) An optimal weight learning machine for handwritten digit image recognition. Signal Process 93(6):1624\u20131638","journal-title":"Signal Process"},{"key":"4479_CR9","unstructured":"Xiao W, Chen H, Liao Q, Poggio T (2018) Biologically-plausible learning algorithms can scale to large datasets. In: Center for brains, minds and machines (CBMM), 2018"},{"issue":"11","key":"4479_CR10","doi-asserted-by":"publisher","first-page":"2256","DOI":"10.1109\/TNNLS.2015.2476656","volume":"27","author":"Y Zhang","year":"2016","unstructured":"Zhang Y, Zhou G, Jin J, Zhao Q, Wang X, Cichocki A (2016) Sparse Bayesian classification of EEG for brain\u2013computer interface. IEEE Trans Neural Netw Learn Syst 27(11):2256\u20132267","journal-title":"IEEE Trans Neural Netw Learn Syst"},{"issue":"6","key":"4479_CR11","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/79.543975","volume":"13","author":"TK Moon","year":"1996","unstructured":"Moon TK (1996) The expectation-maximization algorithm. IEEE Signal Process Mag 13(6):47\u201360","journal-title":"IEEE Signal Process Mag"},{"key":"4479_CR12","doi-asserted-by":"crossref","unstructured":"Zivkovic Z (2004) Improved adaptive Gaussian mixture model for background subtraction. In: Proceedings of the 17th international conference on pattern recognition, 2004. ICPR 2004, vol. 2. IEEE, pp 28\u201331","DOI":"10.1109\/ICPR.2004.1333992"},{"issue":"2","key":"4479_CR13","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/5.18626","volume":"77","author":"LR Rabiner","year":"1989","unstructured":"Rabiner LR (1989) A tutorial on hidden Markov models and selected applications in speech recognition. Proc IEEE 77(2):257\u2013286","journal-title":"Proc IEEE"},{"key":"4479_CR14","doi-asserted-by":"crossref","unstructured":"Lee H, Grosse R, Ranganath R, Ng AY (2009) Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. In: Proceedings of the 26th annual international conference on machine learning, 2009. ACM, pp 609\u2013616","DOI":"10.1145\/1553374.1553453"},{"key":"4479_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-5053-4","volume-title":"A theory of creative thinking: construction and verification of the dual circulation model","author":"K He","year":"2017","unstructured":"He K (2017) A theory of creative thinking: construction and verification of the dual circulation model. Springer, New York"},{"issue":"6","key":"4479_CR16","doi-asserted-by":"publisher","first-page":"1320","DOI":"10.1109\/72.471375","volume":"6","author":"B Igelnik","year":"1995","unstructured":"Igelnik B, Pao Y-H (1995) Stochastic choice of basis functions in adaptive function approximation and the functional-link net. IEEE Trans Neural Netw 6(6):1320\u20131329","journal-title":"IEEE Trans Neural Netw"},{"key":"4479_CR17","doi-asserted-by":"publisher","first-page":"326","DOI":"10.1109\/PGEC.1965.264137","volume":"3","author":"TM Cover","year":"1965","unstructured":"Cover TM (1965) Geometrical and statistical properties of systems of linear inequalities with applications in pattern recognition. IEEE Trans Electron Comput 3:326\u2013334","journal-title":"IEEE Trans Electron Comput"},{"key":"4479_CR18","volume-title":"Neural networks and learning machines","author":"SS Haykin","year":"2009","unstructured":"Haykin SS, Haykin SS, Haykin SS, Haykin SS (2009) Neural networks and learning machines. Pearson, Upper Saddle River"},{"key":"4479_CR19","volume-title":"Elements of artificial neural networks","author":"K Mehrotra","year":"1997","unstructured":"Mehrotra K, Mohan CK, Ranka S (1997) Elements of artificial neural networks. MIT Press, Cambridge"},{"issue":"1","key":"4479_CR20","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TSMC.1979.4310076","volume":"9","author":"N Otsu","year":"1979","unstructured":"Otsu N (1979) A threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern 9(1):62\u201366","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"4479_CR21","doi-asserted-by":"publisher","first-page":"358","DOI":"10.1016\/j.ins.2014.02.073","volume":"277","author":"G Peters","year":"2014","unstructured":"Peters G (2014) Rough clustering utilizing the principle of indifference. Inf Sci 277:358\u2013374","journal-title":"Inf Sci"},{"key":"4479_CR22","unstructured":"LeCun Y, Cortes C, Burges C (2010) MNIST handwritten digit database, vol 2. AT&T Labs [Online]. \nhttp:\/\/yann.lecun.com\/exdb\/mnist"},{"key":"4479_CR23","first-page":"2579","volume":"9","author":"LVD Maaten","year":"2008","unstructured":"Maaten LVD, Hinton G (2008) Visualizing data using t-SNE. J Mach Learn Res 9:2579\u20132605","journal-title":"J Mach Learn Res"},{"key":"4479_CR24","unstructured":"Zhou Y, Gu K, Huang T (2018) Unsupervised representation adversarial learning network: from reconstruction to generation. arXiv preprint \narXiv:1804.07353"},{"key":"4479_CR25","unstructured":"Chen X, Duan Y, Houthooft R, Schulman J, Sutskever I, Abbeel P (2016) Infogan: interpretable representation learning by information maximizing generative adversarial nets. In: Advances in neural information processing systems, 2016, pp 2172\u20132180"},{"key":"4479_CR26","doi-asserted-by":"publisher","first-page":"99","DOI":"10.3389\/fncom.2015.00099","volume":"9","author":"PU Diehl","year":"2015","unstructured":"Diehl PU, Cook M (2015) Unsupervised learning of digit recognition using spike-timing-dependent plasticity. Front Comput Neurosci 9:99","journal-title":"Front Comput Neurosci"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04479-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-019-04479-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-019-04479-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,5]],"date-time":"2020-10-05T15:26:24Z","timestamp":1601911584000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-019-04479-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,13]]},"references-count":26,"journal-issue":{"issue":"18","published-print":{"date-parts":[[2020,9]]}},"alternative-id":["4479"],"URL":"https:\/\/doi.org\/10.1007\/s00521-019-04479-0","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2019,9,13]]},"assertion":[{"value":"30 December 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 August 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 September 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"In the present work, we have not used any material from previously published. So we have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}