Table des matières
MLPfit : a simple and powerful tool for Multi-Layer Perceptrons
Acknowledgments
Part one: Multi-Layer Perceptrons
The Multi-Layer Perceptron...
Multi-Layer Perceptrons...
Applications
« Training » the neural network
The standard minimization method
Properties
A toy example
Unconstrained minimization methods (1)
Steepest descent (Cauchy 1847)
Quadratic methods
Example on the toy problem
The « hybrid » method (1)
Which method for which problem ?
Summary of part 1
Part two: The MLPfit package (1)
MLPfit 1.33
Precision
Speed/Memory
User interfaces
Code organization
Platforms
« Text » interface
Code interface
The LabVIEW interface
The PAW interface
PAW: classification
PAW: Function approximation
The Windows interface
Part three: Examples of applications
Some examples
Fit of a 1d histogram
Correction of the position measurement in the ATLAS electromagnetic calorimeter
WW -> 4q in ALEPH
Hand-written digits recognition
References
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