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Bachelor-Vortrag: Robust Design of Adaptive ANC Systems Considering Self-Induced Sound
Dienstag, 24. November 2020
In addition to passive attenuation, Active Noise Control (ANC) offers a practical way to reduce the power of disturbing noise. Especially in modern headphones this technology finds increasing popularity. Adaptive filters promise a better ANC than time-variant filters since they adjust to a changing environment. Though, they suffer from high sensitivity towards noises caused by the user himself, like speaking or impact sounds. Those noises are called self-induced sounds (SIS) in the following.
This thesis covers the Kalman-Filter as adaptive filter in a feedforward ANC-system. It outperforms other adaptive algorithms concerning different disturbances on the system, like self-induced sounds. The goal of this thesis is the development of noise estimators and methods in order to reduce the disturbing influence of self-induced sounds on adaption.
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