@article{eprints2396,
            year = {2006},
           title = {A scale-free neural network for modelling neurogenesis },
           pages = {71 -- 75},
          number = {1},
          volume = {371},
           month = {November},
          author = {Juan I. Perotti and Francisco A. Tamarit and Sergio A. Cannas},
            note = {LAWNP 2005: IX Latin American Workshop on Nonlinear Phenomena },
       publisher = {Elsevier},
         journal = {Physica A: Statistical Mechanics and its Applications},
        abstract = {In this work we introduce a neural network model for associative memory based on a diluted Hopfield model, which grows through a neurogenesis algorithm that guarantees that the final network is a small-world and scale-free one. We also analyze the storage capacity of the network and prove that its performance is larger than that measured in a randomly dilute network with the same connectivity. },
             url = {http://eprints.imtlucca.it/2396/},
        keywords = {Neural networks; Scale-free networks; Strong dilution}
}