5 papers
A recurrent neural network with ever changing synapses
M. Heerema, W. A. van Leeuwen
A recurrent neural network with noisy input is studied analytically, on the basis of a Discrete Time Master Equation. The latter is derived from a biologically realizable learning…
Probing the basins of attraction of a recurrent neural network
M. Heerema, W. A. van Leeuwen
A recurrent neural network is considered that can retrieve a collection of patterns, as well as slightly perturbed versions of this `pure' set of patterns via fixed points of its d…
Derivation of Hebb's rule
M. Heerema, W. A. van Leeuwen
On the basis of the general form for the energy needed to adapt the connection strengths of a network in which learning takes place, a local learning rule is found for the changes…
Damage spreading transition in glasses: a probe for the ruggedness of the configurational landscape
M. Heerema, F. Ritort
We consider damage spreading transitions in the framework of mode-coupling theory. This theory describes relaxation processes in glasses in the mean-field approximation which are k…
Damage spreading in the mode-coupling equations for glasses
M. Heerema, F. Ritort
We examine the problem of damage spreading in the off-equilibrium mode coupling equations. The study is done for the spherical -spin model introduced by Crisanti, Horner and Som…