The zero attraction affine projection algorithm (ZA-APA) achieves better performance in terms of convergence rate and steady state error than standard APA when the system is sparse. It uses l1 norm penalty to exploit sparsity of the channel. The performance of ZA-APA depends on the value of zero attractor controller. Moreover a fixed attractor controller is not suitable for varying sparsity environment. This paper proposes an optimal adaptive zero attractor controller based on Mean Square Deviation (MSD) error to work in variable sparsity environment. Experiments were conducted to prove the suitability of the proposed algorithm for identification of unknown variable sparse system.

Mordenite-zeolite supported Ca-Cu and Ba-Cu catalysts (Ca-Cu/MOR and Ba-Cu MOR) were successfully fabricated for direct decomposition of both NF3 and N2O gases contained in waste gas stream of (semiconductor) electronics industry. N2O conversion rates of Ca-Cu and Ba-Cu catalysts were 79 and 86%, respectively, at 700°C and 1 atm under space velocity of 5000 h–1. The Ca-Cu catalyst was especially noteworthy in that its capability of converting N2O could be maintained even after its exposure to co-feeding NF3 gas constituent in the waste gas stream. Compositional and surface morphological analyses of the Ca-Cu and Ba-Cu catalysts were made before and after exposure to the waste gas stream to examine any noticeable degradation or change of the catalysts. Unlike Ba-Cu catalyst, SiO2 constituent of the Ca-Cu catalyst was found to remain immune to the NF3-cofeeding waste gas stream, casting a positive prospect for superior and steady N2O decomposition performance via maintenance of its structural integrity.