| Safe Haskell | None |
|---|
Hopfield.Analysis
- computeErrorIndependentPats :: HopfieldData -> Double
- computeErrorSuperAttractor :: HopfieldData -> Double
- computeErrorIndependentPatsNumbers :: Int -> Int -> Double
- computeErrorSuperAttractorNumbers :: Int -> Int -> Int -> Double
- patternsToNeuronsRatioFromError :: Double -> Double
- minNumberOfNeurons :: Int -> Double -> Int
- maxNumberOfPatterns :: Int -> Double -> Int
Documentation
computeErrorIndependentPats :: HopfieldData -> DoubleSource
Computes the probability of error for one element given a hopfield data structure. Note that I claim that the actuall error of probability depends on this, but is not the whole term The assumption is that the patterns which were used to train the network are independent.
computeErrorSuperAttractor :: HopfieldData -> DoubleSource
computes the error of a super attractor of a hopfield network. The assumption is that there is only one super attractor and the other patterns are independent.
computeErrorIndependentPatsNumbers :: Int -> Int -> DoubleSource
computeErrorSuperAttractorNumbers :: Int -> Int -> Int -> DoubleSource
computeErrorSuperAttractorNumbers d p n
Computes the probability of error for a super attractor with degree d, in
a Hopfield network with n neurons, which has been trained with p patterns.
The assumption is that the other patterns are independent
for mathematical derivation of the equation, see report.
patternsToNeuronsRatioFromError :: Double -> DoubleSource
minNumberOfNeurons :: Int -> Double -> IntSource
maxNumberOfPatterns :: Int -> Double -> IntSource