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Artykuły w czasopismach na temat "Multi-layer perceptrons"
Racca, Robert. "Can periodic perceptrons replace multi-layer perceptrons?" Pattern Recognition Letters 21, nr 12 (listopad 2000): 1019–25. http://dx.doi.org/10.1016/s0167-8655(00)00057-x.
Pełny tekst źródłaGarcı́a-Pedrajas, N., D. Ortiz-Boyer i C. Hervás-Martı́nez. "Cooperative coevolution of generalized multi-layer perceptrons". Neurocomputing 56 (styczeń 2004): 257–83. http://dx.doi.org/10.1016/j.neucom.2003.09.004.
Pełny tekst źródłaTSENG, YUEN-HSIEN, i JA-LING WU. "Decoding Reed-Muller codes by multi-layer perceptrons". International Journal of Electronics 75, nr 4 (październik 1993): 589–94. http://dx.doi.org/10.1080/00207219308907134.
Pełny tekst źródłaBuchholz, Sven, i Gerald Sommer. "On Clifford neurons and Clifford multi-layer perceptrons". Neural Networks 21, nr 7 (wrzesień 2008): 925–35. http://dx.doi.org/10.1016/j.neunet.2008.03.004.
Pełny tekst źródłaMirzai, A. R., A. Higgins i D. Tsaptsinos. "Techniques for the minimisation of multi-layer perceptrons". Engineering Applications of Artificial Intelligence 6, nr 3 (czerwiec 1993): 265–77. http://dx.doi.org/10.1016/0952-1976(93)90069-a.
Pełny tekst źródłaEgmont-Petersen, Michael, Jan L. Talmon, Arie Hasman i Anton W. Ambergen. "Assessing the importance of features for multi-layer perceptrons". Neural Networks 11, nr 4 (czerwiec 1998): 623–35. http://dx.doi.org/10.1016/s0893-6080(98)00031-8.
Pełny tekst źródłaRoque, Antonio Muñoz San, Carlos Maté, Javier Arroyo i Ángel Sarabia. "iMLP: Applying Multi-Layer Perceptrons to Interval-Valued Data". Neural Processing Letters 25, nr 2 (15.02.2007): 157–69. http://dx.doi.org/10.1007/s11063-007-9035-z.
Pełny tekst źródłaVlachos, D. S. "A Local Supervised Learning Algorithm For Multi-Layer Perceptrons". Applied Numerical Analysis & Computational Mathematics 1, nr 2 (grudzień 2004): 535–39. http://dx.doi.org/10.1002/anac.200410016.
Pełny tekst źródłaMoustafa, Essam B., i Ammar Elsheikh. "Predicting Characteristics of Dissimilar Laser Welded Polymeric Joints Using a Multi-Layer Perceptrons Model Coupled with Archimedes Optimizer". Polymers 15, nr 1 (2.01.2023): 233. http://dx.doi.org/10.3390/polym15010233.
Pełny tekst źródłaXi, Yan Hui, i Hui Peng. "Training Multi-Layer Perceptrons with the Unscented Kalman Particle Filter". Advanced Materials Research 542-543 (czerwiec 2012): 745–48. http://dx.doi.org/10.4028/www.scientific.net/amr.542-543.745.
Pełny tekst źródłaRozprawy doktorskie na temat "Multi-layer perceptrons"
Zhao, Lenny. "Uncertainty prediction with multi-layer perceptrons". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape3/PQDD_0018/MQ55733.pdf.
Pełny tekst źródłaCairns, Graham Andrew. "Learning with analogue VLSI multi-layer perceptrons". Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296901.
Pełny tekst źródłaPapadopoulos, Georgios. "Theoretical issues and practical considerations concerning confidence measures for multi-layer perceptrons". Thesis, University of Edinburgh, 2000. http://hdl.handle.net/1842/12753.
Pełny tekst źródłaShepherd, Adrian John. "Novel second-order techniques and global optimisation methods for supervised training of multi-layer perceptrons". Thesis, University College London (University of London), 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321662.
Pełny tekst źródłaCollobert, Ronan. "Algorithmes d'Apprentissage pour grandes bases de données". Paris 6, 2004. http://www.theses.fr/2004PA066063.
Pełny tekst źródłaShao, Hang. "A Fast MLP-based Learning Method and its Application to Mine Countermeasure Missions". Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23512.
Pełny tekst źródłaCoughlin, Michael J., i n/a. "Calibration of Two Dimensional Saccadic Electro-Oculograms Using Artificial Neural Networks". Griffith University. School of Applied Psychology, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030409.110949.
Pełny tekst źródłaCoughlin, Michael J. "Calibration of Two Dimensional Saccadic Electro-Oculograms Using Artificial Neural Networks". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365854.
Pełny tekst źródłaThesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Applied Psychology
Griffith Health
Full Text
Dunne, R. A. "Multi-layer perceptron models for classification". Thesis, Dunne, R.A. (2003) Multi-layer perceptron models for classification. PhD thesis, Murdoch University, 2003. https://researchrepository.murdoch.edu.au/id/eprint/50257/.
Pełny tekst źródłaPower, Phillip David. "Non-linear multi-layer perceptron channel equalisation". Thesis, Queen's University Belfast, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.343086.
Pełny tekst źródłaKsiążki na temat "Multi-layer perceptrons"
Ma, Zhe. Explanation by general rules extracted from trained multi-layer perceptrons. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1996.
Znajdź pełny tekst źródłaPeeling, S. M. Experiments in isolated digit recognition using the multi-layer perceptron. [London: HMSO, 1987.
Znajdź pełny tekst źródłaLont, Jerzy B. Analog CMOS implementatrion of a multi-layer perceptron with nonlinear synapses. Kontanz: Hartung-Gorre, 1994.
Znajdź pełny tekst źródłaShepherd, Adrian J. Second-order methods for neural networks: Fast and reliable training methods for multi-layer perceptrons. London: Springer, 1997.
Znajdź pełny tekst źródłaZheng, Gonghui. Design and evaluation of a multi-output-layer perceptron. [s.l: The Author], 1996.
Znajdź pełny tekst źródłaHarrison, R. F. The multi-layer perceptron as an aid to the early diagnosis of myocardial infarction. Sheffield: University of Sheffield, Dept. of Control Engineering, 1990.
Znajdź pełny tekst źródłaMa, Zhe. Dynamic query algorithms for human-computer interaction based on information gain and the multi-layer perceptron. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1996.
Znajdź pełny tekst źródłaShepherd, Adrian J. Second-Order Methods for Neural Networks: Fast and Reliable Training Methods for Multi-Layer Perceptrons. Springer, 2014.
Znajdź pełny tekst źródłaShepherd, Adrian J. Second-Order Methods for Neural Networks: Fast and Reliable Training Methods for Multi-Layer Perceptrons. Springer London, Limited, 2012.
Znajdź pełny tekst źródłaDissertation: Autonomous Construction of Multi Layer Perceptron Neural Networks. Storming Media, 1997.
Znajdź pełny tekst źródłaCzęści książek na temat "Multi-layer perceptrons"
Kruse, Rudolf, Christian Borgelt, Frank Klawonn, Christian Moewes, Matthias Steinbrecher i Pascal Held. "Multi-Layer Perceptrons". W Texts in Computer Science, 47–81. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5013-8_5.
Pełny tekst źródłaKruse, Rudolf, Sanaz Mostaghim, Christian Borgelt, Christian Braune i Matthias Steinbrecher. "Multi-layer Perceptrons". W Texts in Computer Science, 53–124. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-42227-1_5.
Pełny tekst źródłaConan-Guez, Brieuc, i Fabrice Rossi. "Phoneme Discrimination with Functional Multi-Layer Perceptrons". W Classification, Clustering, and Data Mining Applications, 157–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-642-17103-1_16.
Pełny tekst źródłaBo, Liefeng, Ling Wang i Licheng Jiao. "Training Multi-layer Perceptrons Using MiniMin Approach". W Computational Intelligence and Security, 909–14. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596448_135.
Pełny tekst źródłaGoldberg, Yoav. "From Linear Models to Multi-layer Perceptrons". W Neural Network Methods for Natural Language Processing, 37–39. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-031-02165-7_3.
Pełny tekst źródłaArce, Fernando, Erik Zamora, Gerardo Hernández, Javier M. Antelis i Humberto Sossa. "Recognizing Motor Imagery Tasks Using Deep Multi-Layer Perceptrons". W Machine Learning and Data Mining in Pattern Recognition, 468–82. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-96133-0_35.
Pełny tekst źródłaOrtigosa, E. M., P. M. Ortigosa, A. Cañas, E. Ros, R. Agís i J. Ortega. "FPGA Implementation of Multi-layer Perceptrons for Speech Recognition". W Field Programmable Logic and Application, 1048–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45234-8_117.
Pełny tekst źródłaTanahashi, Yusuke, Kazumi Saito i Ryohei Nakano. "Model Selection and Weight Sharing of Multi-layer Perceptrons". W Lecture Notes in Computer Science, 716–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11554028_100.
Pełny tekst źródłaKöksal, Fatih, Ethem Alpaydyn i Günhan Dündar. "Weight Quantization for Multi-layer Perceptrons Using Soft Weight Sharing". W Artificial Neural Networks — ICANN 2001, 211–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-44668-0_30.
Pełny tekst źródłaLappalainen, Harri, i Antti Honkela. "Bayesian Non-Linear Independent Component Analysis by Multi-Layer Perceptrons". W Advances in Independent Component Analysis, 93–121. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0443-8_6.
Pełny tekst źródłaStreszczenia konferencji na temat "Multi-layer perceptrons"
Marchesi, M., G. Orlandi, F. Piazza, L. Pollonara i A. Uncini. "Multi-layer perceptrons with discrete weights". W 1990 IJCNN International Joint Conference on Neural Networks. IEEE, 1990. http://dx.doi.org/10.1109/ijcnn.1990.137772.
Pełny tekst źródłaCoe, Brian. "Multi-layer Perceptrons for Subvocal Recognition". W 2017 IEEE 29th International Conference on Tools with Artificial Intelligence (ICTAI). IEEE, 2017. http://dx.doi.org/10.1109/ictai.2017.00054.
Pełny tekst źródłaHauger, S., i T. Windeatt. "ECOC and boosting with multi-layer perceptrons". W Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. IEEE, 2004. http://dx.doi.org/10.1109/icpr.2004.1334565.
Pełny tekst źródłaYamany, Waleed, Mohammed Fawzy, Alaa Tharwat i Aboul Ella Hassanien. "Moth-flame optimization for training Multi-Layer Perceptrons". W 2015 11th International Computer Engineering Conference (ICENCO). IEEE, 2015. http://dx.doi.org/10.1109/icenco.2015.7416360.
Pełny tekst źródłaAlboaneen, Dabiah Ahmed, Huaglory Tianfield i Yan Zhang. "Glowworm Swarm Optimisation for Training Multi-Layer Perceptrons". W UCC '17: 10th International Conference on Utility and Cloud Computing. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3148055.3148075.
Pełny tekst źródłaRitschel, W., T. Pfeifer i R. Grob. "Rating of pattern classifications in multi-layer perceptrons". W the 1994 ACM symposium. New York, New York, USA: ACM Press, 1994. http://dx.doi.org/10.1145/326619.326684.
Pełny tekst źródłaBernardo-Torres, Abraham, i Pilar Gomez-Gil. "One-step forecasting of seismograms using multi-layer perceptrons". W 2009 6th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE 2009). IEEE, 2009. http://dx.doi.org/10.1109/iceee.2009.5393349.
Pełny tekst źródłaKaban, Ata. "Compressive Learning of Multi-layer Perceptrons: An Error Analysis". W 2019 International Joint Conference on Neural Networks (IJCNN). IEEE, 2019. http://dx.doi.org/10.1109/ijcnn.2019.8851743.
Pełny tekst źródłaBuhrke, E. R., i J. L. LoCicero. "Fast learning for multi-layer perceptrons using statistical techniques". W [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 1992. http://dx.doi.org/10.1109/icassp.1992.225887.
Pełny tekst źródłaZheng, Lilei, Ying Zhang i Vrizlynn L. L. Thing. "Understanding multi-layer perceptrons on spatial image steganalysis features". W 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC). IEEE, 2017. http://dx.doi.org/10.1109/apsipa.2017.8282181.
Pełny tekst źródłaRaporty organizacyjne na temat "Multi-layer perceptrons"
Chen, B., T. Hickling, M. Krnjajic, W. Hanley, G. Clark, J. Nitao, D. Knapp, L. Hiller i M. Mugge. Multi-Layer Perceptrons and Support Vector Machines for Detection Problems with Low False Alarm Requirements: an Eight-Month Progress Report. Office of Scientific and Technical Information (OSTI), styczeń 2007. http://dx.doi.org/10.2172/922310.
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