Gap structure of the local field in symmetric Q Ising neural networks
D. Bollé, G. M. Shim · Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics · 2002
The time evolution of the local field in symmetric Q-Ising neural networks is studied for arbitrary Q. In particular, the structure of the noise and the appearance of gaps in the probability distribution are discussed. Results are presented for several values of Q and compared with numerical simulations.