  Continuous-time Hopfield network has been an important focus of research area
since 1980s whose applications vary from image restoration to combinatorial
optimization from control engineering to associative memory systems. On the
other hand, in wireless communications systems literature, power control has
been intensively studied as an essential mechanism for increasing the system
performance. A fully distributed power control algorithm (DPCA), called Sigmoid
DPCA, is presented by Uykan in [10] and [11], which is obtained by discretizing
the continuous-time system. In this paper, we present a Sigmoid-based
"Signal-to-Interference Ratio, (SIR)" balancing dynamic networks, called
Sgm"SIR"NN, which includes both the Sigmoid power control algorithm (SgmDPCA)
and the Hopfield neural networks, two different areas whose scope of interest,
motivations and settings are completely different. It's shown that the
Sgm"SIR"N5C5C5C5C5CN exhibits features which are generally attributed to
Hopfield Networks. Computer simulations show the effectiveness of the proposed
network as compared to traditional Hopfield Network.
