Publication | Closed Access
Construction of neural nets using the radon transform
166
Citations
2
References
1989
Year
EngineeringMachine LearningNeural Networks (Machine Learning)Feedforward Neural NetValue Function ApproximationRecurrent Neural NetworkSocial SciencesApproximation TheoryGood ApproximationComputer ScienceNeural Networks (Computational Neuroscience)L/sub 2/Deep LearningNeural Architecture SearchComputational NeuroscienceRadon TransformNeuronal NetworkApproximation MethodBrain-like Computing
The authors present a method for constructing a feedforward neural net implementing an arbitrarily good approximation to any L/sub 2/ function over (-1, 1)/sup n/. The net uses n input nodes, a single hidden layer whose width is determined by the function to be implemented and the allowable mean square error, and a linear output neuron. Error bounds and an example are given for the method.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
| Year | Citations | |
|---|---|---|
Page 1
Page 1