{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T14:06:26Z","timestamp":1771509986606,"version":"3.50.1"},"publisher-location":"Cham","reference-count":12,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030372767","type":"print"},{"value":"9783030372774","type":"electronic"}],"license":[{"start":{"date-parts":[[2020,1,1]],"date-time":"2020-01-01T00:00:00Z","timestamp":1577836800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020]]},"DOI":"10.1007\/978-3-030-37277-4_25","type":"book-chapter","created":{"date-parts":[[2020,3,20]],"date-time":"2020-03-20T15:02:39Z","timestamp":1584716559000},"page":"213-221","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["A Fast Approximation of the Hyperbolic Tangent When Using Posit Numbers and Its Application to Deep Neural Networks"],"prefix":"10.1007","author":[{"given":"Marco","family":"Cococcioni","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Federico","family":"Rossi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emanuele","family":"Ruffaldi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sergio","family":"Saponara","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,3,21]]},"reference":[{"key":"25_CR1","unstructured":"Pedamonti D (2018) Comparison of non-linear activation functions for deep neural networks on MNIST classification task. arXiv:1804.02763"},{"key":"25_CR2","unstructured":"Nair V, Hinton GE (2010) Rectified linear units improve restricted Boltzmann machines. In: 27th International conference on international conference on machine learning (ICML) 2010, pp 807\u2013814"},{"key":"25_CR3","unstructured":"K\u00f6ster U et al (2017) Flexpoint: an adaptive numerical format for efficient training of deep neural networks. In: NIPS 2017, pp 1740\u20131750"},{"key":"25_CR4","doi-asserted-by":"crossref","unstructured":"Popescu V et al (2018) Flexpoint: predictive numerics for deep learning. In: IEEE symposium on computer arithmetics, 2018","DOI":"10.1109\/ARITH.2018.8464801"},{"key":"25_CR5","unstructured":"\u201cNVIDIA TURING GPU Architecture, graphics reinvented\u201d, White paper n. WP-09183-001_v01, pp 1\u201380, 2018"},{"key":"25_CR6","doi-asserted-by":"crossref","unstructured":"Malossi A et al (2018) The transprecision computing paradigm: concept, design, and applications. In: IEEE DATE 2018, pp 1105\u20131110","DOI":"10.23919\/DATE.2018.8342176"},{"key":"25_CR7","doi-asserted-by":"crossref","unstructured":"Cococcioni M, Rossi F, Ruffaldi E, Saponara S (2019) Novel arithmetics to accelerate machine learning classifiers in autonomous driving applications. In: IEEE ICECS 2019, Genoa, Italy, 27\u201329 Nov 2019","DOI":"10.1109\/ICECS46596.2019.8965031"},{"key":"25_CR8","doi-asserted-by":"crossref","unstructured":"Cococcioni M, Ruffaldi E, Saponara S (2018) Exploiting posit arithmetic for deep neural networks in autonomous driving applications. IEEE automotive 2018, pp 1\u20136","DOI":"10.23919\/EETA.2018.8493233"},{"issue":"2","key":"25_CR9","first-page":"71","volume":"4","author":"JL Gustafson","year":"2017","unstructured":"Gustafson JL, Yonemoto IT (2017) Beating floating point at its own game: posit arithmetic. Supercomput Front Innov 4(2):71\u201386","journal-title":"Supercomput Front Innov"},{"issue":"11","key":"25_CR10","doi-asserted-by":"publisher","first-page":"2278","DOI":"10.1109\/5.726791","volume":"86","author":"Y LeCun","year":"1998","unstructured":"LeCun Y, Bottou L, Bengio Y, Haffner P (1998) Gradient-based learning applied to document recognition. Proc IEEE 86(11):2278\u20132324","journal-title":"Proc IEEE"},{"key":"25_CR11","unstructured":"LeCun Y, Jackel L, Bottou L, Brunot A, Cortes C, Denker J, Drucker H, Guyon I, Muller U, Sackinger E, Simard P, Vapnik V (1995) Comparison of learning algorithms for handwritten digit recognition. In: Fogelman F, Gallinari P (eds) International conference on artificial neural networks, Paris. EC2 and Cie, pp 53\u201360."},{"key":"25_CR12","unstructured":"Xiao H, Rasul K, Vollgraf R (2017) Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms. arXiv:1708.07747"}],"container-title":["Lecture Notes in Electrical Engineering","Applications in Electronics Pervading Industry, Environment and Society"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-37277-4_25","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,3,21]],"date-time":"2020-03-21T02:03:55Z","timestamp":1584756235000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-37277-4_25"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020]]},"ISBN":["9783030372767","9783030372774"],"references-count":12,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-37277-4_25","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"value":"1876-1100","type":"print"},{"value":"1876-1119","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020]]},"assertion":[{"value":"21 March 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ApplePies","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications in Electronics Pervading Industry, Environment and Society","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Pisa","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 September 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"applepies2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}