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An adaptive algorithm is an algorithm that changes its behavior at the time it is run, [1] based on information available and on a priori defined reward mechanism (or criterion). Such information could be the story of recently received data, information on the available computational resources, or other run-time acquired (or a priori known ...
This makes it very hard (if not impossible) to choose a learning rate that guarantees stability of the algorithm (Haykin 2002). The Normalised least mean squares filter (NLMS) is a variant of the LMS algorithm that solves this problem by normalising with the power of the input. The NLMS algorithm can be summarised as:
SMI determines the adaptive antenna array weights directly, unlike the algorithms of Applebaum and Widrow. [1] A detailed explanation of the adaptive techniques introduced above can be found here: Least Mean Squares Algorithm; Sample Matrix Inversion Algorithm; Recursive Least Square Algorithm; Conjugate gradient method; Constant Modulus Algorithm
The MDF algorithm is based on the fact that convolutions may be efficiently computed in the frequency domain (thanks to the fast Fourier transform). However, the algorithm differs from the fast LMS algorithm in that block size it uses may be smaller than the filter length. If both are equal, then MDF reduces to the FLMS algorithm.
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Kernel adaptive filters implement a nonlinear transfer function using kernel methods. [1] In these methods, the signal is mapped to a high-dimensional linear feature space and a nonlinear function is approximated as a sum over kernels, whose domain is the feature space.
Space-time adaptive processing (STAP) is a signal processing technique most commonly used in radar systems. It involves adaptive array processing algorithms to aid in target detection. Radar signal processing benefits from STAP in areas where interference is a problem (i.e. ground clutter , jamming , etc.).
An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimization algorithm. Because of the complexity of the optimization algorithms, almost all adaptive filters are digital filters .