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1

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

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2

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

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3

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

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4

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

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5

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

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6

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

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7

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

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8

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

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9

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

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10

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

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11

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

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12

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

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13

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

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14

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.

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15

Deep Learning. MIT Press, 2019.

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