activity
20002009
most citedParallel dynamics of disordered Ising spin systems on finitely connected random graphs

64 citations · 297 across the 11 of their papers we have counts for

collaborators

11 papers

cond-mat.dis-nn2009★ 31 cited

Parallel dynamics of disordered Ising spin systems on finitely connected directed random graphs with arbitrary degree distributions

Kazushi Mimura, A. C. C. Coolen

We study the stochastic parallel dynamics of Ising spin systems defined on finitely connected directed random graphs with arbitrary degree distributions, using generating functiona…

physics.soc-ph2007★ 5 cited

Generating functional analysis of minority games with inner product strategy definitions

A. C. C. Coolen, N. Shayeghi

We use generating functional methods to solve the so-called inner product versions of the minority game (MG), with fake and/or real market histories, by generalizing the theory dev…

cond-mat.dis-nn2005★ 40 cited

Finitely connected vector spin systems with random matrix interactions

A. Coolen, N. S. Skantzos, I. Perez Castillo +4

We use finite connectivity equilibrium replica theory to solve models of finitely connected unit-length vectorial spins, with random pair-interactions which are of the orthogonal m…

cond-mat.dis-nn2005★ 30 cited

Dynamical replica analysis of disordered Ising spin systems on finitely connected random graphs

J. P. L. Hatchett, I. Pérez Castillo, A. C. C. Coolen +1

We study the dynamics of macroscopic observables such as the magnetization and the energy per degree of freedom in Ising spin models on random graphs of finite connectivity, with r…

cond-mat.dis-nn2004★ 37 cited

Analytic solution of attractor neural networks on scale-free graphs

I. Pérez Castillo, B. Wemmenhove, J. P. L. Hatchett +3

We study the influence of network topology on retrieval properties of recurrent neural networks, using replica techniques for diluted systems. The theory is presented for a network…

cond-mat.dis-nn2004★ 9 cited

Slowly evolving geometry in recurrent neural networks I: extreme dilution regime

B. Wemmenhove, N. S. Skantzos, A. C. C. Coolen

We study extremely diluted spin models of neural networks in which the connectivity evolves in time, although adiabatically slowly compared to the neurons, according to stochastic…