Identyfikatory
Warianty tytułu
Konferencja
Proceedings of the 2 nd EAA International Symposium on Hydroacoustics 24-27 May 1999, Gdańsk-Jurata POLAND
Języki publikacji
Abstrakty
An algorithm for detection/identification of underwater objects is proposed. The algorithm is based upon the classification ability of a simple multi-layer neural network, also called a Perceptron. A signal recorded by a hydrophone and preprocessed by a computer is supplied to the ANN, which classifies it according to the possessed information encoded within its structure and an array of weighs. Analysis of effectiveness is conducted depending on the variables pertaining to the neural network.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
161--166
Opis fizyczny
Bibliogr. 19 poz., rys.
Twórcy
autor
- Naval Academy, ul. Śmidowicza 17, Gdynia, POLAND
- Maritime University of Szczecin
autor
- Maritime University of Szczecin, ul. Zielona 7, Szczecin, POLAND
- Naval Academy, ul. Śmidowicza 17, Gdynia, POLAND
Bibliografia
- [1] J. Balicki, M Przyborski, A Stateczny. Sea object identification with neural networks application. Zeszyty Naukowe AMW Gdynia, pp. 5-18, (1997).
- [2] M. Barski, W. Jędruch, J. Żurada, Sztuczne sieci neuronowe. Wydawnictwo Naukowe PWN, Warszawa 1996.
- [3] M.Bouvet, S.C. Schwartz, Underwater Noises: Statistical Modeling Detection and Normalization; JASA, Vol. 83, (pp. 1023- 1033) 1988.
- [4] P. Devijver, J. Kittler, Pattern Recognition: A Statistical Approach, Prentice-Hall, 1982.
- [5] H.Demuth, M Beale, Neural Network Toolbox - for use with MATLAB. The Math Works Inc., 1994.
- [6] R.O. Duda, P.E. Hart, Pattern classificatton and scene analysis. John Wiley & Sons, New York 1986.
- [7] G. Grelowska, P. Bittner, I. Gloza, Experimental investigation of the underwater acoustical disturbances by the moving ship. Proceedings of the IX symposium on hydroacoustics, Gdynia-Jurata 2-5.06.1992, pp. 125-132, (1992).
- [8] D.J. Hand, Discrimination and classification. Wiley and Sons, New York 1981.
- [9] W. Kiciński, Method of shipping noise recognition, Proceedings of the international symposium on hydroacoustics and ultrasonics, Gdańsk-Jurata 12-16.05.1997, pp. 157-162, (1997). 160.
- [10] E. Kozaczka, G. Grelowska, J. Gloza, Determmation of the ship detection area in the coastal region, Proceedings of the international symposium on hydroacoustics and ultrasonics, Gdańsk-Jurata 12-16.05.1997, pp. 169-172, (1997).
- [11] J.L. Kulikowski, Cybernetyczne systemy rozpoznawania, PWN, Warszawa 1972.
- [12] S. Osowski, Sieci neuronowe w ujęciu algorytmicznym, Wydawnictwo Naukowo Techniczne, Warszawa 1996.
- [13] Z. Paszofta, Zastosowanie metody Bayes'a w identyfikacji wielospektralnych danych teledetekcyjnych. Rozprawa doktorska, Olsztyn ART 1983.
- [14] M Przyborski., Neural method for identification of moving objects for the needs of the Navy. Doctoral dissertation, Polish Naval Academy, Gdynia 1998.
- [15] J. Schurmann, Paitern Classificanon, A unifled view of statistical and neural approaches, A Wiley-Interscience Publication, 1996.
- [16] J. Szabatin, Podstawy teorii sygnałów, Wydawnictwa Komunikacji i Łączności, Warszawa 1990.
- [17] Z. Świątnicki, R Wantoch-Rekowski, Neural Networks: Introduction, Bellona, warszawa 1999.
- [18] J.T.Tou, R.C. Gonzalez. Pattern Recognition Principles, Addison Wesley Publ. Co., Reading, Ma. 1983.
- [19] A Zahalka, J. Principe, Transieni detection using neural networks: the search for the desired signal, in Advanced Neural Information Proc. Systems 5, Ed. Hanson, Cowan, Giles, pp. 688-695, (1993).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-24499bab-65de-4e1a-98e3-29cc29389227