A lattice network for signal representation using Gaussian basis functions and max-energy paradigm

Describes two novel schemes for efficient representation of 1-D and 2-D signals using Gaussian basis functions (BFs). Special methods are required since the Gaussian functions are nonorthogonal. The first method employs a paradigm of maximum energy reduction interlaced with the A* heuristic search. The second method uses an adaptive lattice system to find the optimal projections of the BFs onto the signal, and a lateral-vertical suppression network to select the most efficient representation in terms of data compression