Information Technology Journal1812-56381812-5646Asian Network for Scientific Information10.3923/itj.2014.661.668LiHongminHeYigangSunYichuang42014134For implementing wavelet transform in analog hardware systems
with very low power consumption and small size, a particle swarm optimization
method is employed in the approximating of wavelet functions. First, utilizing
the least-squares error criterion, a general mathematical model for approximating
wavelet functions is established. Then the technique of L_{2} approximation
based on Particle Swarm Optimization (PSO) is presented, which is more attractive.
These techniques are compared by means of a worked example, involving some wavelet
approximation. The L_{2} approximation approach based on PSO is shown
to exhibit superior performance.]]>Karel, J.M.H., S.A.P. Haddad, S. Hiseni and R.L. Westra,2012Gurrola-Navarro, M.A. and G. Espinosa-Flores-Verdad,2010Haddad, S.A.P., S. Bagga and W.A. Serdijn,2005Karel, J.M.H., R.L.M. Peeters, R.L. Westra, S.A.P. Haddad and W.A. Serdijn,2005Baker Jr., G.A.,1975Bultheel, A. and M.V. Barel,1986Kennedy, J. and R. Eberhart,1995Mallat, S.,1999Walnut, D.F.,2004Hongmin, L., H. Yigang and Y. Sun,2008Li, H., H. Gang, G. Zhang and G. Guo,2010