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Books on the topic 'Neural networks (Computer science) Building'

Author: Grafiati

Published: 4 June 2021

Last updated: 12 February 2022

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1

Building neural networks. ACM Press, 1996.

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2

Molina, Alfonso Hernán. Building up a neural network sociotechnical constituency: A contribution to the formulation of the UK strategy. Research Centre for Social Sciences, University of Edinburgh, 1990.

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3

Blum, Adam. Neural networks in C++: An object-oriented framework for building connectionist systems. Wiley, 1992.

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4

Blum, Adam. Neural networks in C [plus plus]: An object-oriented framework for building connectionist systems. Wiley, 1992.

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5

Dominique, Valentin, and Edelman Betty, eds. Neural networks. Sage Publications, 1999.

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6

Neural networks. Palgrave, 2000.

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7

Bischof, Horst. Pyramidal neural networks. Lawrence Erlbaum Associates, 1995.

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8

Kwon, Seoyun J. Artificial neural networks. Nova Science Publishers, 2010.

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9

Hoffmann, Norbert. Simulating neural networks. Vieweg, 1994.

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10

Baram, Yoram. Nested neural networks. National Aeronautics and Space Administration, Ames Research Center, 1988.

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11

Hu, Xiaolin, and P. Balasubramaniam. Recurrent neural networks. InTech, 2008.

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12

Artificial neural networks. McGraw-Hill, 1997.

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13

Digital neural networks. PTR Prentice Hall, 1993.

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14

Kung, S. Y. Digital neural networks. Institute of Electrical andElectronics Engineers, 1993.

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15

Neural networks: A tutorial. PTR Prentice Hall, 1993.

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16

Zhang, Yunong. Zhang neural networks and neural-dynamic method. Nova Science Publishers, 2009.

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17

Caudill, Maureen. Understanding neural networks: Computer explorations. MIT Press, 1993.

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18

Neural logic networks: A new class of neural networks. World Scientific, 1995.

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19

Neural networks in computer intelligence. McGraw-Hill, 1994.

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20

Fu, LiMin. Neural networks in computer intelligence. McGraw-Hill, 1994.

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21

M, Izhikevich Eugene, ed. Weakly connected neural networks. Springer, 1997.

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22

Neural networks and simulation methods. M. Dekker, 1994.

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23

Gurney, Kevin. An introduction to neural networks. Routledge, 1999.

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24

K, Mohan Chilukuri, and Ranka Sanjay, eds. Elements of artificial neural networks. MIT Press, 1997.

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25

An introduction to neural networks. UCL Press, 1997.

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26

J, Marks Robert, ed. Neural smithing: Supervised learning in feedforward artificial neural networks. The MIT Press, 1999.

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27

Gupta, Madan M. Static and Dynamic Neural Networks. John Wiley & Sons, Ltd., 2004.

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28

service), SpringerLink (Online, ed. Sensitivity analysis for neural networks. Springer, 2010.

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29

Zhang, Yi, and Zhou Jiliu, eds. Subspace learning of neural networks. CRC Press, 2011.

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30

Ansari, Shamshad. Building Computer Vision Applications Using Artificial Neural Networks. Apress, 2020. http://dx.doi.org/10.1007/978-1-4842-5887-3.

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31

McGeever, John. Generalisation in ontogenic neural networks. University College Dublin, 1995.

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32

Focus on artificial neural networks. Nova Science Publishers, 2011.

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33

1931-, Haykin Simon S., ed. Neural networks and learning machines. 3rd ed. Prentice Hall, 2008.

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34

Foundations of neural networks. Addison-Wesley, 1990.

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35

Tatiana, Baidyk, Wunsch Donald C, and SpringerLink (Online service), eds. Neural Networks and Micromechanics. Springer-Verlag Berlin Heidelberg, 2010.

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36

Haykin, S. S. Neural networks: A comprehensive foundation. Prentice Hall, 1994.

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37

Neural networks: Methodology and applications. Springer, 2005.

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38

The promise of neural networks. Springer-Verlag, 1993.

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39

Principles of artificial neural networks. 2nd ed. World Scientific, 2007.

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40

Haykin, Simon. Neural networks: A comprehensive foundation. 2nd ed. Pearson Education, 1999.

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41

Haykin, S. S. Neural networks: A comprehensive foundation. Prentice Hall International, 1994.

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42

Callan, Robert. The essence of neural networks. Prentice Hall Europe, 1998.

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43

Haykin, S. S. Neural networks: A comprehensive foundation. 2nd ed. Prentice Hall, 1999.

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44

Ramacher, Ulrich. VLSI Design of Neural Networks. Springer US, 1991.

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45

P, Morgan David. Neural networks and speech processing. Kluwer Academic Publishers, 1991.

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46

Patterson, Dan W. Artificial neural networks: Theory and applications. Prentice Hall, 1996.

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47

Wiggins, Vince L. Neural networks: A primer. Armstrong Laboratory, Air Force Systems Command, 1991.

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48

Huang, Su-Yun. Statistical Learning: Building Knowledge from Data. Wiley & Sons, Incorporated, John, 2014.

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49

1931-, Taylor John, and UNICOM Seminars, eds. Neural networks. A. Waller, 1995.

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50

Maass, Wolfgang, and Christopher M. Bishop. Pulsed Neural Networks. MIT Press, 2001.

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