Comparison of Class 1 and Class 2 frequency domain matrix and vector estimation filters with adaptive FIR filters

Class 1 and 2 frequency domain block matrix and vector estimation filters are compared with adaptive FIR (finite impulse response) filters based on gradient search algorithms, including Newton, steepest descent, and LMS (least mean square). It is shown that the algorithm of the Class 1 filter considered has the same form as the Wiener-Hopf equation. It is found that the Class 2 estimation filter has the form of an adaptive FIR filter based on Newton's method. Simulations show that utilizing smoothing techniques can further improve the performance and efficiency of the Class 2 estimation filter.<
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