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On training feedforward neural networks

https://doi.org/10.1007/bf02898040
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/bf02875373openalex-snapshot
State generators and complex neural memories
inferredcites →https://doi.org/10.2307/2312103openalex-snapshot
Principles of Neurodynamics.
inferredcites →https://doi.org/10.7551/mitpress/5236.001.0001openalex-snapshot
Parallel Distributed Processing

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Two corner classification algorithms for training the Kak feedforward neural network
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Comparison of learning and generalization capabilities of the Kak and the Backpropagation algorithms
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New algorithms for training feedforward neural networks
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Quantum Neural Computing
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Reactivity Surveillance in a Nuclear Reactor by Using a Layered Artificial Neural Network
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Evolutionary Neurocontrol: A Smart Method for Global Optimization of Low-Thrust Trajectories
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Modular Approaches for Designing Feedforward Neural Networks to Solve Classification Problems.
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Unary Coding for Neural Network Learning
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The Algebra of Two Dimensional Patterns
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A Survey of Prediction Using Social Media
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Memory Capacity of a Random Neural Network
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Neural Network Capacity for Multilevel Inputs
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Memory Capacity of Neural Networks using a Circulant Weight Matrix
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User Profile Relationships using String Similarity Metrics in Social Networks
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Training of CC4 Neural Network with Spread Unary Coding
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Learning Based on CC1 and CC4 Neural Networks
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Order Effects for Queries in Intelligent Systems
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Neural Networks with Complex and Quaternion Inputs
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