Measurement, composition and inversion of orthogonal representations of memoryless nonlinearities

The authors present a technique for identifying, composing and inverting memoryless nonlinearities using orthogonal polynomial representations. They start by pointing out a disadvantage of conventional nonlinear system characterization and inversion techniques based on power series models, then show that the approach has an advantage over the conventional power series inversion method. Examples are given for the sinusoidal input case using Chebyshev polynomials.< >