Design of a near-optimal adaptive filter in digital signal processor for active noise control

2008 ◽  
Vol 22 (1) ◽  
pp. 43-54
Author(s):  
S. M. Yang ◽  
K. F. Lee ◽  
S. E. Tsai
Keyword(s):  
Adaptive Filter ◽  
Digital Signal Processor ◽  
Noise Control ◽  
Active Noise Control ◽  
Digital Signal ◽  
Active Noise ◽  
Signal Processor

Integration of a Quantitative Feedback Theory (QFT)-Based Active Noise Canceller and 3D Audio Processor to Headsets

2007 ◽  
Vol 129 (5) ◽  
pp. 567-576 ◽  
Author(s):  
Mingsian R. Bai ◽  
Jianliang Lin
Keyword(s):  
Digital Signal Processor ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Digital Signal ◽  
Quantitative Feedback Theory ◽  
Processing Technologies ◽  
3D Audio ◽  
Active Noise ◽  
Spatial Sound Reproduction

This paper seeks to enhance the quality of spatial sound reproduction by integrating two advanced signal processing technologies, active noise control (ANC) and three-dimensional (3D) audio, to a headset. The ANC module of the headset is designed based on the quantitative feedback theory (QFT), which is a unified theory that emphasizes the use of feedback for achieving the desired system performance tolerances in the face of plant uncertainties and plant disturbances. Performance, stability, and robustness of the closed-loop system have been taken into account in the loop-shaping procedure within a general framework of the QFT. On the other hand, 3D audio processing algorithms including the head-related-transfer-function and the reverberator are realized on the platform of a fixed-point digital signal processor. Listening tests were conducted to evaluate the proposed system in terms of various subjective performance indices. The experimental results revealed that the 3D headset is capable of delivering superior rendering quality of localization and spaciousness, with the aid of the ANC module.

Real-Time Subspace Identification and Optimal Control for Active Noise Cancellation

2004 ◽  
Author(s):  
Harin Pongpairoj ◽  
Vineet Chaparala ◽  
Farzad Pourboghrat
Keyword(s):  
Optimal Control ◽  
Real Time ◽  
Digital Signal Processor ◽  
Adaptive Estimation ◽  
Active Noise Control ◽  
Digital Signal ◽  
Subspace Identification ◽  
Controlled System ◽  
Active Noise ◽  
Feedback Active Noise Control

In this paper, a combination of a novel recursive subspace identification and receding horizon optimal control is developed for real-time implementation, via a digital signal processor (DSP), using only input-output measurements. The proposed recursive strategy can be parameterized in terms of recursive approximation of subspace intersections and adaptive estimation of state sequences. The proposed integrated modeling-control strategy can be implemented, in real time, with minimum knowledge of the controlled system. Actual hardware experiments on feedback active noise control problem in a duct have been carried out in order to verify the performance of the proposed methodology.

scholarly journals Application of adaptive filter to active noise control

1999 ◽  
Vol 32 (2) ◽  
pp. 4402-4406
Author(s):  
Chuanguang Li ◽  
Bingnan Pei ◽  
Xiuling Han
Keyword(s):  
Adaptive Filter ◽  
Noise Control ◽  
Active Noise Control ◽  
Active Noise

scholarly journals Multiple Iteration of Weight Updates for Least Mean Square Adaptive Filter in Active Noise Control Application

2017 ◽  
Vol 95 ◽  
pp. 14006
Author(s):  
Rahimie Mustafa ◽  
Anuar Mikdad Muad ◽  
Shahrizal Jelani ◽  
Ahmad Nur Alifa Abdul Razap
Keyword(s):  
Adaptive Filter ◽  
Noise Control ◽  
Active Noise Control ◽  
Mean Square ◽  
Least Mean Square ◽  
Active Noise ◽  
Control Application
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