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Existing conventional online secondary path modeling algorithms for active noise control system have the characteristic that the operation of the controller and the modeling process of the secondary path are mutually interfered.
The design of an active noise control system involves several steps.
This latter control technique, called iterative learning control, can significantly increase the performance of a feedback active noise control system.
Such a setup represents a noise control system based on the principles of the active elasticity control of piezoelectric materials.
The results obtained here provide some insights into the efficient implementation of the algorithm in an active noise control system.
Natural algorithms have been considered as a method of finding optimal secondary loudspeaker positions in an active noise control system.
Similar(14)
An adaptive nonlinear neuro-controller with an integrated evaluation algorithm for nonlinear active noise control systems is proposed to attenuate the nonlinear and non-Gaussian noises.
This device complements other active noise control systems currently proposed.
Forms of the LMS algorithm have been implemented recently in active noise control systems.
Technological development has made it possible to implement digital active noise control systems in real time.
Additionally, dedicated active noise control systems for the control of broadband rolling noise are developed.
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