title: A simple method for designing efficient small-world neural networks.
abstract: Small-world neural networks, as well as diluted Hopfield networks, are constructed by using matrix decomposition and a connection elimination strategy. It is shown that, to a certain extent, eliminating the unimportant synaptic couplings does not degrade the network performance. Numerical simulations give strong evidence that the small-world and diluted neural networks, by consuming a small fraction of connections, can perform as well as full-connected ones. The proposed method is simple but efficient and also potentially significant for the applications of neural circuits.
authors: Pengsheng
authors: P
authors: Zheng
authors: Wansheng
authors: W
authors: Tang
authors: Jianxiong
authors: J
authors: Zhang
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D010364:Pattern Recognition, Visual; D011932:Reading; D013569:Synapses / Q000502:physiology