Fast convergemce algorithms for active noise control in vehicles
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When reference signal for the FxLMS algorithm is taken from an acoustic sensor convergence can be very slow due to great eigen value spread. Using a non acoustic sensor, Such as a tachometer, cancellation of narrow band noise in the sensed fundamental frequency and harmonically related ones can be achieved very fast, although other periodic noises and underline broad band noise will remain.




Backward prediction errors resulting at the various stages of an adaptive lattice predictor(ALP) represent a a time-domain orthogonalization of the input signal.An ALP structure, with the acoustic reference has input signal, before a FxLMS makes up the FxGAL algorithm. Due to the orthogonalization, FxGAL can be significantly faster compared to FxLMS with reference from a microphone. When compared to FxLMS with tachometer signal, it is not faster but it can cancel every periodic noise, independently of the harmonical relation between them, as well as the underlined broad band noise. Comparative results between FxLMS (with acoustic and nonacoustic reference) and FxGAL are presented.
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