Bücher zum Thema „Chaotic Recurrent Neural Networks“

Hu, Xiaolin, und P. Balasubramaniam. Recurrent neural networks. Rijek, Crotia: InTech, 2008.

Hammer, Barbara. Learning with recurrent neural networks. London: Springer London, 2000. http://dx.doi.org/10.1007/bfb0110016.

ElHevnawi, Mahmoud, und Mohamed Mysara. Recurrent neural networks and soft computing. Rijeka: InTech, 2012.

K, Tan K., Hrsg. Convergence analysis of recurrent neural networks. Boston: Kluwer Academic Publishers, 2004.

Yi, Zhang, und K. K. Tan. Convergence Analysis of Recurrent Neural Networks. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4757-3819-3.

Whittle, Peter. Neural nets and chaotic carriers. Chichester: Wiley, 1998.

Graves, Alex. Supervised Sequence Labelling with Recurrent Neural Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012.

Graves, Alex. Supervised Sequence Labelling with Recurrent Neural Networks. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24797-2.

Neural nets and chaotic carriers. 2. Aufl. London: Imperial College Press, 2010.

Derong, Liu, Hrsg. Qualitative analysis and synthesis of recurrent neural networks. New York: Marcel Dekker, Inc., 2002.

Chen, Wen. Recurrent neural networks applied to robotic motion control. Ottawa: National Library of Canada, 2002.

Rovithakis, George A., und Manolis A. Christodoulou. Adaptive Control with Recurrent High-order Neural Networks. London: Springer London, 2000. http://dx.doi.org/10.1007/978-1-4471-0785-9.

Bianchi, Filippo Maria, Enrico Maiorino, Michael C. Kampffmeyer, Antonello Rizzi und Robert Jenssen. Recurrent Neural Networks for Short-Term Load Forecasting. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70338-1.

Kuan, Chung-Ming. Forecasting exchange rates using feedforward and recurrent neural networks. Champaign: University of Illinois at Urbana-Champaign, 1993.

Kuan, Chung-Ming. Forecasting exchange rates using feedforward and recurrent neural networks. [Urbana, Ill.]: College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1992.

Manganaro, G. Cellular neural networks: Chaos, complexity, and VLSI processing. Berlin: Springer, 1999.

Rovithakis, George A. Adaptive control with recurrent high-order neural networks: Theory and industrial applications. London: Springer, 2000.

Rovithakis, George A. Adaptive Control with Recurrent High-order Neural Networks: Theory and Industrial Applications. London: Springer London, 2000.

Manganaro, Gabriele. Cellular Neural Networks: Chaos, Complexity and VLSI Processing. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999.

Priesol, Adrian J. Dynamics of a chaotic neural network in response to a sustained stimulus. Toronto: Dept. of Computer Science, University of Toronto, 1991.

Common LISP modules: Artificial intelligence in the era of neural networks and chaos theory. New York: Springer-Verlag, 1991.

Rietman, Ed. Exploring the geometry of nature: Computer modeling of chaos, fractals, cellular automata, and neural networks. Blue Ridge Summit, PA: Windcrest, 1989.

The nonlinear workbook: Chaos, fractals, cellular automata, neural networks, genetic algorithms, gene expression programming, support vector machine, wavelets, hidden Markov models, Fuzzy logic with C++, Java and SymbolicC++ programs. 5. Aufl. New Jersey: World Scientific, 2011.

1925-, Yamaguchi Masaya, Hrsg. Towards the harnessing of chaos: A collection of contributions based on lectures presented at the seventh Toyota Conference, Mikkabi, Shizuoka, Japan, October 31 to November 3, 1993. Amsterdam: Elsevier, 1994.

Xiaomo, Jiang, Hrsg. Intelligent infrastructure: Neural networks, wavelets, and chaos theory for intelligent transportation systems and smart structures. Boca Raton, FL: CRC Press, 2008.

Medsker, Larry, und Lakhmi C. Jain, Hrsg. Recurrent Neural Networks. CRC Press, 1999. http://dx.doi.org/10.1201/9781420049176.

Hu, Xiaolin, und P. Balasubramaniam, Hrsg. Recurrent Neural Networks. InTech, 2008. http://dx.doi.org/10.5772/68.

Aihara, Kazuyuki. Chaotic Neural Networks. Cambridge University Press, 2004.

Hammer, Barbara. Learning with Recurrent Neural Networks. Springer, 2000.

Yi, Zhang. Convergence Analysis of Recurrent Neural Networks. Springer, 2013.

R, Medsker L., und Jain L. C, Hrsg. Recurrent neural networks: Design and applications. Boca Raton, Fla: CRC Press, 2000.

ElHefnawi, Mahmoud, Hrsg. Recurrent Neural Networks and Soft Computing. InTech, 2012. http://dx.doi.org/10.5772/2296.

Whittle, Peter. Neural Nets and Chaotic Carriers. Wiley & Sons, Incorporated, John, 2000.

Graves, Alex. Supervised Sequence Labelling with Recurrent Neural Networks. Springer, 2012.

Supervised Sequence Labelling With Recurrent Neural Networks. Springer, 2012.

Recurrent Neural Networks for Temporal Data Processing. InTech, 2011.

Brunner, Daniel, Miguel C. Soriano und Guy Van der Sande. Photonic Reservoir Computing: Optical Recurrent Neural Networks. de Gruyter GmbH, Walter, 2019.

Cardot, Hubert, Hrsg. Recurrent Neural Networks for Temporal Data Processing. InTech, 2011. http://dx.doi.org/10.5772/631.

1965-, Kolen John F., und Kremer Stefan C. 1968-, Hrsg. A field guide to dynamical recurrent networks. New York: IEEE Press, 2001.

(Editor), John F. Kolen, und Stefan C. Kremer (Editor), Hrsg. A Field Guide to Dynamical Recurrent Networks. Wiley-IEEE Press, 2001.

Knowledge Acquisition and Representation in Recurrent Neural Networks. World Scientific Publishing Company, 2005.

Yi, Zhang, und K. K. Tan. Convergence Analysis of Recurrent Neural Networks (Network Theory and Applications). Springer, 2003.

Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability. Wiley, 2001.

Mandic, Danilo P., und Jonathon A. Chambers. Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability. Wiley & Sons, Incorporated, John, 2003.

(Editor), Larry Medsker, und Lakhmi C. Jain (Editor), Hrsg. Recurrent Neural Networks: Design and Applications (The Crc Press International Series on Computational Intelligence). CRC, 1999.

Branko, Souček, und IRIS Group, Hrsg. Dynamic, genetic, and chaotic programming: The sixth-generation. New York: Wiley, 1992.

Michel, Anthony, und Derong Liu. Qualitative Analysis and Synthesis of Recurrent Neural Networks (Pure and Applied Mathematics). CRC, 2002.

Bianchi, Filippo Maria Maria, Enrico Maiorino, Michael C. Kampffmeyer, Antonello Rizzi und Robert Jenssen. Recurrent Neural Networks for Short-Term Load Forecasting: An Overview and Comparative Analysis. Springer, 2017.

Soucek, Branko, und The IRIS Group. Dynamic, Genetic, and Chaotic Programming: The Sixth-Generation (Sixth Generation Computer Technologies). Wiley-Interscience, 1992.

Kostadinov, Simeon. Recurrent Neural Networks with Python Quick Start Guide: Sequential learning and language modeling with TensorFlow. Packt Publishing, 2018.