6 papers
Synchronous versus sequential updating in the three-state Ising neural network with variable dilution
D. Bolle', R. Erichsen, T. Verbeiren
The three-state Ising neural network with synchronous updating and variable dilution is discussed starting from the appropriate Hamiltonians. The thermodynamic and retrieval proper…
Multiplicative versus additive noise in multi-state neural networks
D. Bolle, J. Busquets Blanco, T. Verbeiren
The effects of a variable amount of random dilution of the synaptic couplings in Q-Ising multi-state neural networks with Hebbian learning are examined. A fraction of the couplings…
The signal-to-noise analysis of the Little-Hopfield model revisited
D. Bolle, J. Busquets Blanco, T. Verbeiren
Using the generating functional analysis an exact recursion relation is derived for the time evolution of the effective local field of the fully connected Little-Hopfield model. It…
A spherical Hopfield model
D. Bolle, Th. M. Nieuwenhuizen, I. Perez Castillo +1
We introduce a spherical Hopfield-type neural network involving neurons and patterns that are continuous variables. We study both the thermodynamics and dynamics of this model. In…
The Blume-Emery-Griffiths neural network: dynamics for arbitrary temperature
D. Bolle, J. Busquets Blanco, G. M. Shim +1
The parallel dynamics of the fully connected Blume-Emery-Griffiths neural network model is studied for arbitrary temperature. By employing a probabilistic signal-to-noise approach,…
Thermodynamics of fully connected Blume-Emery-Griffiths neural networks
D. Bolle, T. Verbeiren
The thermodynamic and retrieval properties of fully connected Blume-Emery-Griffiths networks, storing ternary patterns, are studied using replica mean-field theory. Capacity-temper…