{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T00:10:05Z","timestamp":1737418205230,"version":"3.33.0"},"publisher-location":"Berlin, Heidelberg","reference-count":14,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540746935"},{"type":"electronic","value":"9783540746959"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2007]]},"DOI":"10.1007\/978-3-540-74695-9_71","type":"book-chapter","created":{"date-parts":[[2007,9,13]],"date-time":"2007-09-13T13:32:27Z","timestamp":1189690347000},"page":"690-698","source":"Crossref","is-referenced-by-count":0,"title":["Performance Analysis of MLP-Based Radar Detectors in Weibull-Distributed Clutter with Respect to Target Doppler Frequency"],"prefix":"10.1007","author":[{"given":"Raul","family":"Vicen-Bueno","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maria P.","family":"Jarabo-Amores","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manuel","family":"Rosa-Zurera","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Roberto","family":"Gil-Pita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Mata-Moya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"71_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1007\/11550907_145","volume-title":"Artificial Neural Networks: Formal Models and Their Applications \u2013 ICANN 2005","author":"D. Mata-Moya De la","year":"2005","unstructured":"De la Mata-Moya, D., et al.: Approximating the Neyman-Pearson Detector for Swerling I Targets with Low Complexity Neural Networks. In: Duch, W., Kacprzyk, J., Oja, E., Zadro\u017cny, S. (eds.) ICANN 2005. LNCS, vol.\u00a03697, pp. 917\u2013922. Springer, Heidelberg (2005)"},{"key":"71_CR2","volume-title":"Detection, Estimation and Modulation Theory","author":"H.L. Trees Van","year":"1997","unstructured":"Van Trees, H.L.: Detection, Estimation and Modulation Theory. John Wiley and Sons, New York (1997)"},{"key":"71_CR3","doi-asserted-by":"crossref","unstructured":"Cheikh, K., Faozi, S.: Application of Neural Networks to Radar Signal Detection in K-distributed Clutter. In: First Int. Symp. on Control, Communications and Signal Processing Workshop Proc., pp. 633\u2013637 (2004)","DOI":"10.1109\/ISCCSP.2004.1296282"},{"key":"71_CR4","doi-asserted-by":"crossref","unstructured":"Farina, A., et al.: Theory of Radar Detection in Coherent Weibull Clutter. In: Farina, A. (ed.) Optimised Radar Processors. IEE Radar, Sonar, Navigation and Avionics, Peter Peregrinus Ltd., London, vol.\u00a01, pp. 100\u2013116 (1987)","DOI":"10.1049\/PBRA001E_ch11"},{"key":"71_CR5","unstructured":"DiFranco, J.V., Rubin, W.L.: Radar Detection, Artech House. U.S.A (1980)"},{"issue":"6","key":"71_CR6","doi-asserted-by":"publisher","first-page":"893","DOI":"10.1109\/TASSP.1987.1165221","volume":"ASSP-35","author":"A. Farina","year":"1987","unstructured":"Farina, A., et al.: Radar Detection in Coherent Weibull Clutter. IEEE Trans. on Acoustics, Speech and Signal Processing\u00a0ASSP-35(6), 893\u2013895 (1987)","journal-title":"IEEE Trans. on Acoustics, Speech and Signal Processing"},{"issue":"11","key":"71_CR7","doi-asserted-by":"publisher","first-page":"296","DOI":"10.1109\/72.80266","volume":"1","author":"D.W. Ruck","year":"1990","unstructured":"Ruck, D.W., et al.: The Multilayer Perceptron as an Approximation to a Bayes Optimal Discriminant Function. IEEE Trans. on Neural Networks\u00a01(11), 296\u2013298 (1990)","journal-title":"IEEE Trans. on Neural Networks"},{"key":"71_CR8","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1109\/SSP.2005.1628609","volume-title":"Proc. IEEE Workshop on Statistical Signal Processing","author":"P. Jarabo-Amores","year":"2005","unstructured":"Jarabo-Amores, P., et al.: Sufficient Condition for an Adaptive System to Aproximate the Neyman-Pearson Detector. In: Proc. IEEE Workshop on Statistical Signal Processing, pp. 295\u2013300. IEEE Computer Society Press, Los Alamitos (2005)"},{"issue":"11","key":"71_CR9","doi-asserted-by":"publisher","first-page":"2846","DOI":"10.1109\/78.650111","volume":"45","author":"P.P. Gandhi","year":"1997","unstructured":"Gandhi, P.P., Ramamurti, V.: Neural Networks for Signal Detection in Non-Gaussian Noise. IEEE Trans. on Signal Processing\u00a045(11), 2846\u20132851 (1997)","journal-title":"IEEE Trans. on Signal Processing"},{"key":"71_CR10","first-page":"3573","volume":"96","author":"D. Andina","year":"1996","unstructured":"Andina, D., Sanz-Gonzalez, J.L.: Comparison of a Neural Network Detector Vs Neyman-Pearson Optimal Detector. Proc. of ICASSP-96, 3573\u20133576 (1996)","journal-title":"Proc. of ICASSP-"},{"key":"71_CR11","volume-title":"Neural Networks. A Comprehensive Foundation","author":"S. Haykin","year":"1999","unstructured":"Haykin, S.: Neural Networks. A Comprehensive Foundation, 2nd edn. Prentice-Hall, London (1999)","edition":"2"},{"key":"71_CR12","doi-asserted-by":"crossref","DOI":"10.1093\/oso\/9780198538493.001.0001","volume-title":"Neural networks for pattern recognition","author":"C.M. Bishop","year":"1995","unstructured":"Bishop, C.M.: Neural networks for pattern recognition. Oxford University Press, New York (1995)"},{"issue":"6","key":"71_CR13","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1109\/72.329697","volume":"5","author":"M.T. Hagan.","year":"1994","unstructured":"Hagan, M.T., Menhaj, M.B.: Training Feedforward Networks with Marquardt Algorithm. IEEE Trans. on Neural Networks\u00a05(6), 989\u2013993 (1994)","journal-title":"IEEE Trans. on Neural Networks"},{"key":"71_CR14","doi-asserted-by":"crossref","unstructured":"Nguyen, D., Widrow, B.: Improving the Learning Speed of 2-layer Neural Networks by Choosing Initial Values of the Adaptive Weights. In: Proc. of the Int. Joint Conf. on Neural Networks, pp. 21\u201326 (1999)","DOI":"10.1109\/IJCNN.1990.137819"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks \u2013 ICANN 2007"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-74695-9_71","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T23:55:22Z","timestamp":1737417322000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-74695-9_71"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2007]]},"ISBN":["9783540746935","9783540746959"],"references-count":14,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-74695-9_71","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2007]]}}}