{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T23:55:53Z","timestamp":1792022153594,"version":"4.4.0"},"reference-count":20,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2013,3,1]],"date-time":"2013-03-01T00:00:00Z","timestamp":1362096000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This paper develops a primitive gas recognition system for discriminating between industrial gas species. The system under investigation consists of an array of eight micro-hotplate-based SnO2 thin film gas sensors with different selectivity patterns. The output signals are processed through a signal conditioning and analyzing system. These signals feed a decision-making classifier, which is obtained via a Field Programmable Gate Array (FPGA) with Very High-Speed Integrated Circuit Hardware Description Language. The classifier relies on a multilayer neural network based on a back propagation algorithm with one hidden layer of four neurons and eight neurons at the input and five neurons at the output. The neural network designed after implementation consists of twenty thousand gates. The achieved experimental results seem to show the effectiveness of the proposed classifier, which can discriminate between five industrial gases.<\/jats:p>","DOI":"10.3390\/s130302967","type":"journal-article","created":{"date-parts":[[2013,3,1]],"date-time":"2013-03-01T13:09:27Z","timestamp":1362143367000},"page":"2967-2985","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":33,"title":["Gas Sensors Characterization and Multilayer Perceptron (MLP) Hardware Implementation for Gas Identification Using a Field Programmable Gate Array (FPGA)"],"prefix":"10.3390","volume":"13","author":[{"given":"Fay\u00e7al","family":"Benrekia","sequence":"first","affiliation":[{"name":"Laboratory of Instrumentation (LINS), Faculty of Electronics and Computers, USTHB PO Box 32, Bab Ezzouar 16111, Algiers, Algeria"},{"name":"Department of Electrical Engineering and Computers, Faculty of Science and Technology, UYFM 26000, Medea, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mokhtar","family":"Attari","sequence":"additional","affiliation":[{"name":"Laboratory of Instrumentation (LINS), Faculty of Electronics and Computers, USTHB PO Box 32, Bab Ezzouar 16111, Algiers, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mounir","family":"Bouhedda","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering and Computers, Faculty of Science and Technology, UYFM 26000, Medea, Algeria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2013,3,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1109\/JSEN.2002.800685","article-title":"SnO2 gas sensing array for combustible and explosive gas leakage recognition","volume":"2","author":"Lee","year":"2002","journal-title":"IEEE Sens. J."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1109\/JSEN.2002.800688","article-title":"Pattern analysis for machine olfaction: A review","volume":"2","year":"2002","journal-title":"IEEE Sens. J."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.snb.2007.02.058","article-title":"A Pattern recognition method for electronic nose based on an olfactory neural network","volume":"125","author":"Fu","year":"2007","journal-title":"Sens. Actuators B Chem."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1109\/JSEN.2009.2020116","article-title":"A bio-inspired pattern recognition system for tin oxide gas sensor applications","volume":"9","author":"Far","year":"2009","journal-title":"IEEE Sens. J."},{"key":"ref_5","first-page":"129","article-title":"Complex measuring system for longtime monitoring and visualization of temperature and toxic gases concentration","volume":"6","author":"Hajovsky","year":"2012","journal-title":"Electron. Electr. Eng."},{"key":"ref_6","first-page":"59","article-title":"Application of the neural classifier for automated detection of extraneous water in milk","volume":"9","author":"Daunoras","year":"2011","journal-title":"Electron. Electr. Eng."},{"key":"ref_7","first-page":"1433","article-title":"A floating point multiplier based FPGA synthesis for neural networks enhancement","volume":"2","author":"Benrekia","year":"2010","journal-title":"Int. J. Eng. Sci. Technol."},{"key":"ref_8","unstructured":"Jang, E.-T., and Chung, W.-Y. (2002, January 8\u201311). 11.6: Electronic Nose Module with System on Chip. Pusan, Korea."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"9179","DOI":"10.3390\/s101009179","article-title":"Development of a portable electronic nose system for the detection and classification of fruity odors","volume":"10","author":"Tang","year":"2010","journal-title":"Sensors"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1109\/JSEN.2002.804360","article-title":"Carbon monoxide detector fabricated on the basis of a tin oxide novel doping method","volume":"2","author":"Mandayo","year":"2002","journal-title":"IEEE Sens. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/S0925-4005(98)00092-6","article-title":"A low power cmos compatible integrated gas sensor using maskless tin oxide sputtering","volume":"49","author":"Yan","year":"1998","journal-title":"Sens. Actuators B Chem."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"277","DOI":"10.1016\/S0925-4005(01)01064-4","article-title":"An integrated gas sensor technology using surface micro-machining","volume":"82","author":"Chan","year":"2002","journal-title":"Sens. Actuators B Chem."},{"key":"ref_13","unstructured":"Gutierrez-Osuna, R., Korah, S., and Perera, A. (2001, January 25\u201330). Multi-Frequency Temperature Modulation for Metal-Oxide Gas Sensors. Washington, DC, USA."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/S0303-2647(96)01660-7","article-title":"Computational parallels between the biological olfactory pathway and its analogue \u2018the electronic nose\u2019: Part II. Sensor-based machine olfaction","volume":"41","author":"Pearce","year":"1997","journal-title":"Biosystems"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Polikar, R., Shinar, R., Honavar, V., Udpa, L., and Porter, M.D. (2001, January 7\u201311). Detection and Identification of Odorants Using an Electronic Nose. Salt Lake City, Utah, USA. Volume 5.","DOI":"10.1109\/ICASSP.2001.940323"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1049\/ip-cds:19990670","article-title":"Electronic noses: A review of signal processing techniques","volume":"146","author":"Hines","year":"1999","journal-title":"IEEE Proc. Circuit Device. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/S1569-190X(03)00044-3","article-title":"Methods to improve prediction performance of ANN models","volume":"11","author":"Yin","year":"2003","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"708","DOI":"10.1016\/S0043-1648(03)00149-2","article-title":"Artificial neural network predictions on erosive wear polymer","volume":"255","author":"Zhang","year":"2003","journal-title":"Wear"},{"key":"ref_19","unstructured":"Alyuda NeuroIntelligence Webpage Available online: http:\/\/www.alyuda.com\/neural-networks-software.htm (accessed on 1 December 2011)."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/JSEN.2008.917124","article-title":"A committee machine gas identification system based on dynamically reconfigurable FPGA","volume":"8","author":"Shi","year":"2008","journal-title":"IEEE Sens. J."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/3\/2967\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:45:14Z","timestamp":1760219114000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/13\/3\/2967"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,3,1]]},"references-count":20,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2013,3]]}},"alternative-id":["s130302967"],"URL":"https:\/\/doi.org\/10.3390\/s130302967","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,3,1]]}}}