Books on the topic 'Backpropagation'

Karazanos, Elias. Temporal learning using time-dependent backpropagation and teacher forcing. Manchester: UMIST, 1997.

Nicolaides, Lena. Thermal-wave slice diffraction tomography with backpropagation and transmission reconstructions. Ottawa: National Library of Canada, 1996.

P, Dhawan Atam, and United States. National Aeronautics and Space Administration., eds. LVQ and backpropagation neural networks applied to NASA SSME data. [Washington, DC: National Aeronautics and Space Administration, 1993.

Gaxiola, Fernando, Patricia Melin, and Fevrier Valdez. New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-34087-6.

Wellington, Charles H. Backpropagation neural network for noise cancellation applied to the NUWES test ranges. Monterey, Calif: Naval Postgraduate School, 1991.

Werbos, Paul J. The roots of backpropagation: From ordered derivatives to neural networksand political forecasting. New York: Wiley, 1994.

N, Sundararajan, and Foo Shou King, eds. Parallel implementations of backpropagation neural networks on transputers: A study of training set parallelism. Singapore: World Scientific, 1996.

Billings, S. A. A comparison of the backpropagation and recursive prediction error algorithms for training neural networks. Sheffield: University of Sheffield, Dept. of Control Engineering, 1990.

Menke, Kurt William. Nonlinear adaptive control using backpropagating neural networks. Monterey, Calif: Naval Postgraduate School, 1992.

Chauvin, Yves, and David E. Rumelhart, eds. Backpropagation. Psychology Press, 2013. http://dx.doi.org/10.4324/9780203763247.

Rumelhart, David E., and Yves Chauvin. Backpropagation: Theory, Architectures, and Applications. Taylor & Francis Group, 2013.

Rumelhart, David E., and Yves Chauvin. Backpropagation: Theory, Architectures, and Applications. Taylor & Francis Group, 2013.

Rumelhart, David E., and Yves Chauvin. Backpropagation: Theory, Architectures, and Applications. Taylor & Francis Group, 2013.

Smith, Joel T. Backpropagation network for gesture recognition. 1996.

Rumelhart, David E., and Yves Chauvin. Backpropagation: Theory, Architectures, and Applications. Taylor & Francis Group, 2013.

(Editor), Yves Chauvin, and David E. Rumelhart (Editor), eds. Backpropagation: Theory, Architectures, and Applications. Lawrence Erlbaum, 1995.

Mnih, Andriy. Learning nonlinear constraints with contrastive backpropagation. 2004.

Backpropagation: Theory, Architectures, and Applications (Developments in Connectionist Theory). Lawrence Erlbaum, 1995.

Nikolaev, Nikolay, and Hitoshi Iba. Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods. Springer, 2006.

Gaxiola, Fernando, Patricia Melin, and Fevrier Valdez. New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks. Springer International Publishing AG, 2016.

Adaptive Learning Of Polynomial Networks Genetic Programming Backpropagation And Bayesian Methods. Springer, 2011.

Gaxiola, Fernando, Patricia Melin, and Fevrier Valdez. New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks. Springer London, Limited, 2016.

The roots of backpropagation: From ordered derivatives to neural networks and political forecasting. New York: Wiley, 1994.

Deep Learning. Cambridge, USA: MIT Press, 2019.

Foo, Shou King. Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism. World Scientific Publishing Co Pte Ltd, 1996.

Foo, Shou King. Parallel Implementations of Backpropagation Neural Networks on Transputers: A Study of Training Set Parallelism. World Scientific Publishing Co Pte Ltd, 1996.

Adaptive Learning of Polynomial Networks: Genetic Programming, Backpropagation and Bayesian Methods (Genetic and Evolutionary Computation). Springer, 2006.

Learn from Scratch Backpropagation Neural Networks Using Python GUI and MariaDB: Hands-On, Step by Step Approach to Understand the Backpropagation Neural Networks for Data Prediction and Data Classification Through Project Based Examples. Independently Published, 2021.