![]() ![]() One method of choosing the interpolators is by a non-linear optimization procedure based only on a priori knowledge of input process. In general, optimal design of interpolator FB requires a priori knowledge of the input process and the system. The interpolators could be chosen to improve convergence rate of the adaptive algorithm. This allows flexibility to choose the interpolators. It is shown that delayless adaptive IFIR FB structure, as a special case of general adaptive IFIR FB, can be obtained by relaxing the orthogonality condition on the basis functions. The delaying structure is obtained by employing orthogonal set of the basis functions for the interpolating FB. Realizations of adaptive IFIR FB structures with delaying and delayless properties are presented. The modeling capabilities and delay properties of the structure are investigated. The IFIR FB models the system impulse response as a linear combination of double indexed set of functions. The IFIR model is a set of cascade of an interpolator and a sparse filter connected in parallel. This paper investigates a generalized adaptive interpolated finite impulse response (IFIR) FB structure. Adaptive filters based on filter bank (FB) techniques have attracted attention recently due to their ability to improve convergence rate and reduce the computational complexity. ![]()
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March 2023
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