Dr. Liu et An. Michel, ROBUSTNESS ANALYSIS AND DESIGN OF A CLASS OF NEURAL NETWORKS WITH SPARSE INTERCONNECTING STRUCTURE, Neurocomputing, 12(1), 1996, pp. 59-76
Citations number
9
Categorie Soggetti
Computer Sciences, Special Topics","Computer Science Artificial Intelligence",Neurosciences
We first conduct an analysis of the robustness Properties of-a class o
f neural networks with applications to associative memories. Specifica
lly, for a network with nominal parameters which stores a set of desir
ed bipolar memories, we establish sufficient conditions under which th
e same set of bipolar memories is also stored in the network with pert
urbed parameters. This result enables us to establish a synthesis proc
edure for neural networks whose stored memories are invariant under pe
rturbations. Our synthesis procedure is capable of generating artifici
al neural networks with prespecified sparsity constraints (on the inte
rconnecting structure) and with nonsymmetric and symmetric interconnec
tion matrices. To demonstrate the applicability of the present results
, we consider several specific examples.