Books on the topic 'Perceptrons'

Murty, M. N., and Rashmi Raghava. Support Vector Machines and Perceptrons. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-41063-0.

Minsky, Marvin Lee. Perceptrons: An Introduction to Computational Geometry. Cambridge, Massachusetts: MIT Press, 1988.

Gorelik, A. L. Sovremennoe sostoi͡a︡nie problemy raspoznavanii͡a︡: Nekotorye aspekty. Moskva: "Radio i svi͡a︡zʹ", 1985.

Bielecki, Andrzej. Models of Neurons and Perceptrons: Selected Problems and Challenges. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-90140-4.

Niemiro, Wojciech. Statystyczne własnosci metody minimalizacji perceptronowej funkcji kryterialnej w dyskryminacji liniowej. Warszawa: In-t Biocybernetyki i Inżynierii Biomedycznej, 2000.

Ma, Zhe. Explanation by general rules extracted from trained multi-layer perceptrons. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1996.

International Conference on Information Acquisition (2004 Hefei Shi, China). ICIA 2004: Proceedings of 2004 International Conference on Information Acquisition : June 21-25, 2004, Hefei, China. Edited by Mei Tao and International Association of Information Acquisition. Piscataway, N.J: IEEE, 2004.

Peeling, S. M. Experiments in isolated digit recognition using the multi-layer perceptron. [London: HMSO, 1987.

P, Banks Stephen. Can Perceptrons find Lyapunov functions?: An algorithmic approach to systems stability. Sheffield: University of Sheffield, Dept. of Control Engineering, 1989.

Glaz, A. B. Parametricheskai͡a︡ i strukturnai͡a︡ adaptat͡s︡ii͡a︡ reshai͡u︡shchikh pravil v zadachakh raspoznavanii͡a︡. Riga: "Zinatne", 1988.

Mokhonʹko, E. Z. Perceptive systems. Moscow: VT͡S AN SSSR, 1991.

Lont, Jerzy B. Analog CMOS implementatrion of a multi-layer perceptron with nonlinear synapses. Kontanz: Hartung-Gorre, 1994.

Shepherd, Adrian J. Second-order methods for neural networks: Fast and reliable training methods for multi-layer perceptrons. London: Springer, 1997.

Bystrov, L. V. Sistema identifika͡tsii parametrov dinamicheskikh sistem dl͡ia personalʹnykh ĖVM. Moskva: Vychislitelʹnyĭ ͡tsentr AN SSSR, 1989.

F, Murray Alan, ed. Analogue imprecision in MLP training. Singapore: World Scientific, 1996.

International Conference on Artificial Intelligence and Information-Control Systems of Robots (4th 1987 Smolenice, Slovakia). Artificial intelligence and information-control systems of robots -87: Proceedings of the Fourth International Conference on Artificial Intelligence and Information-Control Systems of Robots, Smolenice, Czechoslovakia, 19-23 October, 1987. Amsterdam: North-Holland, 1987.

Mäntyjärvi, Jani. Sensor-based context recognition for mobile applications. Espoo [Finland]: VTT Technical Research Centre of Finland, 2003.

Zheng, Gonghui. Design and evaluation of a multi-output-layer perceptron. [s.l: The Author], 1996.

Ma, Zhe. A heuristic for general rule extraction from a multilayer perceptron. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1995.

Harrison, 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.

Harrison, R. F. Neur al networks,heart attack and bayesian decisions: An application oof the Boltzmann perceptron network. Sheffield: University of Sheffield, Dept. of Automatic Control & Systems Engineering, 1994.

Ma, 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.

1941-, Hart Peter E., and Stork David G, eds. Pattern classification. 2nd ed. New York: Wiley, 2001.

Minsky, Marvin, and Seymour A. Papert. Perceptrons. The MIT Press, 2017. http://dx.doi.org/10.7551/mitpress/11301.001.0001.

Vang-Mata, Ruth. Multilayer Perceptrons: Theory and Applications. Nova Science Publishers, Incorporated, 2020.

Vang-Mata, Ruth. Multilayer Perceptrons: Theory and Applications. Nova Science Publishers, Incorporated, 2020.

Frieß, Thilo-Thomas. Perceptrons in kernel feature spaces. University of Sheffield, Dept. of Automatic Control and Systems Engineeringc1998., 1998.

Finite Automata, Pattern Recognition and Perceptrons. Creative Media Partners, LLC, 2023.

Minsky, Marvin Lee, and Seymour Papert. Perceptrons: An Introduction to Computational Geometry. MIT Press, 2017.

Jis Kanji Character Recognition Methods. International Thomson Computer Press, 1997.

Bielecki, Andrzej. Models of Neurons and Perceptrons: Selected Problems and Challenges. Springer, 2019.

Bielecki, Andrzej. Models of Neurons and Perceptrons: Selected Problems and Challenges. Springer, 2018.

Minsky, Marvin Lee, and Seymour Papert. Perceptrons - Expanded Edition: An Introduction to Computational Geometry. The MIT Press, 1987.

Venema, Rienk S. How the perceptron reacts on non-separable classification problems. 1994.

Cheriet, Mohamed, Nawwaf Kharma, Cheng-Lin Liu, and Ching Suen. Character Recognition Systems: A Guide for Students and Practitioners. Wiley & Sons, Incorporated, John, 2007.

Black, Michael. Applying Perceptrons to Speculation in Computer Architecture- Neural Networks in Future Microprocessors. VDM Verlag Dr. Mueller e.K., 2007.

Murty, M. N., and Rashmi Raghava. Support Vector Machines and Perceptrons: Learning, Optimization, Classification, and Application to Social Networks. Springer London, Limited, 2016.

Murty, M. N., and Rashmi Raghava. Support Vector Machines and Perceptrons: Learning, Optimization, Classification, and Application to Social Networks. Springer, 2016.

Shepherd, Adrian J. Second-Order Methods for Neural Networks: Fast and Reliable Training Methods for Multi-Layer Perceptrons. Springer, 2014.

Shepherd, Adrian J. Second-Order Methods for Neural Networks: Fast and Reliable Training Methods for Multi-Layer Perceptrons. Springer London, Limited, 2012.

Artificial Intelligence and Information-control Systems of Robots. Elsevier, 1987.

Golija, Gaja. Tobias Putrih: Perceptron. Hatje Cantz Verlag GmbH & Co KG, 2023.

Tho, Dang Xuan. Perceptron Problem in Neural Network. GRIN Verlag GmbH, 2011.

Dunne, Robert A. Statistical Approach to Neural Networks for Pattern Recognition. Wiley & Sons, Incorporated, John, 2007.

Dunne, Robert A. Statistical Approach to Neural Networks for Pattern Recognition. Wiley & Sons, Incorporated, John, 2006.

Sonnet, Daniel. Neuronale Netze kompakt: Vom Perceptron zum Deep Learning. Springer Vieweg, 2021.

Club, Rocket Baby. Toby's Video Game Puzzle : Machine Learning for Kids: Perceptron. Primedia eLaunch LLC, 2019.

Dissertation: Autonomous Construction of Multi Layer Perceptron Neural Networks. Storming Media, 1997.

Lont, Jerzy B. Analog CMOS implementation of a multi-layer perceptron with nonlinear synapses. 1993.

Ltd, ICON Group. PERCEPTRON, INC.: International Competitive Benchmarks and Financial Gap Analysis (Financial Performance Series). 2nd ed. Icon Group International, 2000.