Abstract
A well known sub-class of neural networks is the single-layer feed-forward neural network, in which all neurons are grouped in one layer [3],[4]. A typical single-layer feed-forward neural network is shown in figure 3.1a.
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References
T.M Heskes and B. Kappen, “Learning processes in neural networks”, Physical Review A, vol. 44, 2718–2726, 1991
T.M. Heskes, E.T.P. Slijpen and B. Kappen, “Learning in neural networks with local minima”, Physical Review A, vol. 46, 5221–523, 1992
R.P. Lippmann, “An Introduction into Computing with Neural Nets”, IEEE ASSP Mag., vol. 4, 4–22, 1987
M.L. Minsky and S.A. Papert, Perceptrons, An Introduction to Computational Geometry, Expanded Edition, Cambridge, MA.: MIT Press, 1988
A. Papoulis, Probability, Random Variables and Stochastic Processes, New York: McGraw-Hill, 1984
D.B. Parker, Learning Logic, Technical Report 47, MIT, 1985
D.E. Rumelhart, G.E. Hinton and RJ. Williams, “Learning internal representations by error propagation”, in Parallel Distributed Processing. Exploration of the microstructure of cognition, vol. 1, Cambridge, MA.: MIT Press, 1986
E.D. Sontag and H.J. Sussmann, “Back Propagation Separates Where Perceptrons Do”, Neural Networks, vol.4, 243–249, 1991
J.J. Shynk and N.J. Bershad, “Steady-State Analysis of a Single-Layer Perceptron Based on a System Identification Model with Bias Terms”, IEEE Trans. Neural Networks, vol.38, 1030–1042, 1991
J.J. Shynk and N.J. Bershad, “Stationary Points and Performance Surfaces of a Perceptron Learning Algorithm for a Nonseparable Data Model”, In Proceedings of the IJCNN (Baltimore), vol. 2, 133–139, 1992
P.J. Werbos, “Backpropagation: Past and Future”, In Proceeding of the IJCNN (San Diego), CA., vol. 1, 343–353, 1988
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Annema, AJ. (1995). Dynamics of Single Layer Nets. In: Feed-Forward Neural Networks. The Springer International Series in Engineering and Computer Science, vol 314. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2337-6_3
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DOI: https://doi.org/10.1007/978-1-4615-2337-6_3
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