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Delta rule

In machine learning, the delta rule is a gradient descent learning rule for updating the weights of the inputs to artificial neurons in a single… 
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Related topics

Related topics

8 relations
Activation functionBackpropagationCatastrophic interferenceFeedforward neural network

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2016
Highly Cited
2016
New Closed-Form Solutions for Optimal Impulsive Control of Spacecraft Relative Motion
This paper addresses energy-optimal guidance and control of satellite relative motion for formation flying and rendezvous using… 
Highly Cited
2009
Highly Cited
2009
Performance Comparison of Multi-layer Perceptron (Back Propagation, Delta Rule and Perceptron) algorithms in Neural Networks
A multilayer perceptron is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate… 
Highly Cited
2008
Highly Cited
2008
Evaluating generalizability and parameter consistency in learning models
Highly Cited
2007
Highly Cited
2007
Application of bacterial foraging technique trained artificial and wavelet neural networks in load forecasting
Highly Cited
2004
Highly Cited
2004
A novel control algorithm for the DG interface to mitigate power quality problems
Distributed Generation (DG) exists in distribution systems and is installed by either the utility or the customers. This paper… 
Highly Cited
2001
Highly Cited
2001
Short-Term Water Demand Forecast Modelling at IIT Kanpur Using Artificial Neural Networks
The efficient operation and management of an existing water supply system require short-term water demand forecasts as inputs… 
Highly Cited
1996
Highly Cited
1996
Mapping Ecological Land Systems and Classification Uncertainties from Digital Elevation and Forest-Cover Data Using Neural Networks
Our approaches in this project emphasized mainly the technical aspects of the land-systems classification problem with neural… 
Highly Cited
1996
Highly Cited
1996
Identification of nonlinear dynamical systems using multilayered neural networks
Highly Cited
1995
Highly Cited
1995
Robustness analysis of radial base function and multi-layered feed-forward neural network models
1985
1985
The delta rule development system for speech synthesis from text
Progress in speech synthesis has been hampered by the lack of rule-writing tools of sufficient flexibility and power. This paper… 
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