Improved Reconstruction Algorithm of Wireless Sensor Network Based on BFGS Quasi-Newton Method

Aiming at the problems of low reconstruction rate and poor precision when reconstructing sparse signals in wireless sensor networks, a signal algorithm based on Limit-Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) quasi-Newton method is proposed. The L-BFGS uses two-loop recursion to find descent direction dk directly by calculating step difference between m adjacent iteration points, matrix Hk approximating inverse Hessian constructed. It solves disadvantages BFGS requiring calculation storage Hk, reduces complexity, improves rate. Finally, experimental results show that has good for solving problem networks.