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.

scholarly journals Integration of Bass Enhancement and Active Noise Control System in Automobile Cabin

2008 ◽  
Vol 2008 ◽  
pp. 1-9 ◽  
Author(s):  
Liang Wang ◽  
Woon Seng Gan ◽  
Sen M. Kuo
Keyword(s):  
Control System ◽  
Noise Suppression ◽  
Noise Control ◽  
Active Noise Control ◽  
Low Frequency ◽  
Audio Signal ◽  
Digital Signal ◽  
Processing Technologies ◽  
Active Noise

With the advancement of digital signal processing technologies, consumers are more concerned with the quality of multimedia entertainment in automobiles. In order to meet this demand, an audio enhancement system is needed to improve bass reproduction and cancel engine noise in the cabins. This paper presents an integrated active noise control system that is based on frequency-sampling filters to track and extract the bass information from the audio signal, and a multifrequency active noise equalizer to tune the low-frequency engine harmonics to enhance the bass reproduction. In the noise cancellation mode, a maximum of 3 dB bass enhancement can be achieved with significant noise suppression, while higher bass enhancement can be achieved in the bass enhance mode. The results show that the proposed system is effective for solving both the bass audio reproduction and the noise control problems in automobile cabins.

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.

Active Noise Cancellation for a Three-Dimensional Enclosure by Using Multiple-Channel Adaptive Control and H∞ Control

1998 ◽  
Vol 120 (4) ◽  
pp. 958-964 ◽  
Author(s):  
M. R. Bai ◽  
Z. Lin
Keyword(s):  
Digital Signal Processor ◽  
Random Noise ◽  
Active Noise Control ◽  
Three Dimensional ◽  
Internal Field ◽  
Least Mean Square ◽  
Control Structures ◽  
Multiple Channel ◽  
Active Noise ◽  
Fxlms Algorithm

Active noise control (ANC) techniques for a three-dimensional enclosure are compared in terms of two control structures and two control algorithms. The multiple-channel filtered-x least-mean-square (FXLMS) algorithm and the H∞ robust control algorithm are employed for controller synthesis. Both feedforward and feedback control structures are compared. The Youla’s parameterization is employed in the formulation of the multiple-channel feedback FXLMS algorithm. The algorithms are implemented using a floating-point digital signal processor (DSP). Experiments are carried out to validate the ANC approaches for attenuation of the internal field in a rectangular wooden box. Position and number of actuators and sensors are also investigated. A broadband random noise and an engine noise are chosen as the primary noises in the experiments. The experimental results indicate that the feedforward structure yields a broader band of attenuation than the feedback structure. The FXLMS control and H∞, control achieve comparable performance.

Broadband Spatially Feedforward Active Noise Control Algorithms Using a Comb Filter

2003 ◽  
Vol 125 (1) ◽  
pp. 18-23
Author(s):  
Mingsian R. Bai ◽  
Jienwen Lai
Keyword(s):  
Digital Signal Processor ◽  
Active Noise Control ◽  
Digital Signal ◽  
Least Square Method ◽  
Least Square ◽  
Comb Filter ◽  
Control Algorithms ◽  
Recursive Filter ◽  
Active Noise ◽  
The Ideal

A controller composed of a nonrecursive filter and a recursive filter is used to approximate the ideal controller for a spatially feedforward duct ANC problem. The nonrecursive part represents the dynamics of the transducer, whereas the recursive part is in the form of a comb filter. The parameters of the comb filter are obtained from the impulse response of the controller by using the least-square method. The comb filter is then cascaded with the nonrecursive part implemented as either a fixed filter or an adaptive filter. In the latter approach, two types of LMS-based algorithms are used. The proposed algorithms are implemented on the platform of a digital signal processor. Experimental results showed that the approximated controller attained 17 dB maximal attenuation in the frequency band 200∼600Hz.

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