Upper bound on pattern storage in feedforward networks (original) (raw)

Constructive proof of efficient pattern storage in the multi-layer perceptron

Michael Manry

1993

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The Capacity of feedforward neural networks

Pierre Baldi

Neural Networks

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Role of Function Complexity and Network Size in the Generalization Ability of Feedforward Networks

leonardo franco

2005

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A Guide for the Upper Bound on the Number of Continuous-Valued Hidden Nodes of a Feed-Forward Network

Y. Wan, Rua-huan Tsaih

Lecture Notes in Computer Science, 2009

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The hidden layer size in feed-forward neural networks: a statistical point of view

Cira Perna

Metron

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Nature of the learning algorithms for feedforward neural networks

Elena Miñana

1996

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Pattern Discrimination Using Feedforward Networks: A Benchmark Study of Scaling Behavior

Thorsteinn Rögnvaldsson

Neural Computation, 1993

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Computational capabilities of feedforward neural networks: the role of the output function

Jose Subirats

Proceedings of the XII CAEPIA

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Multilayer feedforward networks with a nonpolynomial activation function can approximate any function

Moshe Leshno

Neural Networks, 1993

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Functional approximation by feed-forward networks: a least-squares approach to generalization

Andrew Webb

IEEE Transactions on Neural Networks, 1994

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On topology, size and generalization of non-linear feed-forward neural networks

Stephan Rudolph

Neurocomputing, 1997

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Generalization of patterns by identification with polynomial neural network

Ladislav Zjavka

2020

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Storage capacity and learning algorithms for two-layer neural networks

Annette Zippelius

Physical Review A, 1992

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A dynamical model for the analysis and acceleration of learning in feedforward networks

Nicholas Ampazis

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Generalization and Selection of Examples in Feedforward Neural Networks

leonardo franco

Neural Computation, 2000

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Generalization and capacity of extensively large two-layered perceptrons

Michal Rosen-Zvi

Physical Review E, 2002

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Neural Networks Revisited: A Statistical View On Optimisation And Generalisation

Andreas Wendemuth

2003

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A geometric approach to learning in neural networks

Pal Rujan

International Joint Conference on Neural Networks, 1989

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Some nonlinear networks capable of learning a spatial pattern of arbitrary complexity

Steve Chung

Proceedings of the National Academy of Sciences …, 1968

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Bounds on the complexity of neural-network models and comparison with linear methods

Katerina Hlavackova-Schindler

International Journal of Adaptive Control and Signal Processing, 2003

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Pattern classification and associative recall by neural networks

Tzi-dar Chiueh

2012

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On approximate learning by multi-layered feedforward circuits

Bhaskar Dasgupta

2005

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Multilayer feedforward networks are universal approximators

B N

Neural Networks, 1989

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On the capacity of neural networks

Leonardo Cruciani

University of Trieste - arXiv, 2022

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Some Theorems for Feed Forward Neural Networks

Vishwajeet Singh, Vishwajeet Thakur, Kumar Eswaran

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Chapter 5 Approximating Multivariable Functions by Feedforward Neural Nets

Paul Kainen

2013

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On Adaptive Learning Rate That Guarantees Convergence in Feedforward Networks

Laxmidhar Behera

IEEE Transactions on Neural Networks, 2006

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Capabilities and training of feedforward nets

eduardo sontag

1992

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Sample Size Requirements of Feedforward Neural Network Pattern Classifiers

Terrence Fine

Proceedings. IEEE International Symposium on Information Theory, 1993

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Storage capacity of the Tilinglike Learning Algorithm

Mirta Gordon, Arnaud Buhot

2001

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