155 research outputs found

    Infinite non-causality in active cancellation of random noise

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    Active cancellation of broadband random noise requires the detection of the incoming noise with some time advance. In an duct for example this advance must be larger than the delays in the secondary path from the control source to the error sensor. In this paper it is shown that, in some cases, the advance required for perfect noise cancellation is theoretically infinite because the inverse of the secondary path, which is required for control, can include an infinite non-causal response. This is shown to be the result of two mechanisms: in the single-channel case (one control source and one error sensor), this can arise because of strong echoes in the control path. In the multi-channel case this can arise even in free field simply because of an unfortunate placing of sensors and actuators. In the present paper optimal feedforward control is derived through analytical and numerical computations, in the time and frequency domains. It is shown that, in practice, the advance required for significant noise attenuation can be much larger than the secondary path delays. Practical rules are also suggested in order to prevent infinite non-causality from appearing

    Estimation-based synthesis of H∞-optimal adaptive FIR filtersfor filtered-LMS problems

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    This paper presents a systematic synthesis procedure for H∞-optimal adaptive FIR filters in the context of an active noise cancellation (ANC) problem. An estimation interpretation of the adaptive control problem is introduced first. Based on this interpretation, an H∞ estimation problem is formulated, and its finite horizon prediction (filtering) solution is discussed. The solution minimizes the maximum energy gain from the disturbances to the predicted (filtered) estimation error and serves as the adaptation criterion for the weight vector in the adaptive FIR filter. We refer to this adaptation scheme as estimation-based adaptive filtering (EBAF). We show that the steady-state gain vector in the EBAF algorithm approaches that of the classical (normalized) filtered-X LMS algorithm. The error terms, however, are shown to be different. Thus, these classical algorithms can be considered to be approximations of our algorithm. We examine the performance of the proposed EBAF algorithm (both experimentally and in simulation) in an active noise cancellation problem of a one-dimensional (1-D) acoustic duct for both narrowband and broadband cases. Comparisons to the results from a conventional filtered-LMS (FxLMS) algorithm show faster convergence without compromising steady-state performance and/or robustness of the algorithm to feedback contamination of the reference signal

    Modified filtered-x hierarchical lms algorithm with sequential partial updates for active noise control

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    In the field of active noise control (ANC), a popular method is the modified filtered-x LMS algorithm. However, it has two drawbacks: Its computational complexity higher than that of the conventional FxLMS, and its convergence rate that could still be improved. Therefore, we propose an adaptive strategy which aims at speeding up the convergence rate of an ANC system dealing with periodic disturbances. This algorithm consists in combining the organization of the filter weights in a hierarchy of subfilters of shorter length and their sequential partial updates (PU). Our contribution is threefold: (1) we provide the theoretical basis of the existence of a frequency-depend-ent parameter, called gain in step-size. (2) The theoretical upper bound of the step-size is compared with the limit obtained from simulations. (3) Additional experiments show that this strategy results in a fast algorithm with a computational complexity close to that of the conventional FxLMS

    Performance analysis and design of FxLMS algorithm in broadband ANC system with online secondary-path modeling

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    The filtered-x LMS (FxLMS) algorithm has been widely used in active noise control (ANC) systems, where the secondary path is usually estimated online by injecting auxiliary noises. In such an ANC system, the ANC controller and the secondary-path estimator are coupled with each other, which make it difficult to analyze the performance of the entire system. Therefore, a comprehensive performance analysis of broadband ANC systems is not available currently to our best knowledge. In this paper, the convergence behavior of the FxLMS algorithm in broadband ANC systems with online secondary-path modeling is studied. Difference equations which describe the mean and mean square convergence behaviors of the adaptive algorithms are derived. Using these difference equations, the stability of the system is analyzed. Finally, the coupled equations at the steady state are solved to obtain the steady-state excess mean square errors (EMSEs) for the ANC controller and the secondary-path estimator. Computer simulations are conducted to verify the agreement between the simulated and theoretically predicted results. Moreover, using the proposed theoretical analysis, a systematic and simple design procedure for ANC systems is proposed. The usefulness of the theoretical results and design procedure is demonstrated by means of a design example. © 2012 IEEE.published_or_final_versio

    Review of active noise control techniques with emphasis on sound quality enhancement

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    The traditional active noise control design aims to attenuate the energy of residual noise, which is indiscriminative in the frequency domain. However, it is necessary to retain residual noise with a specified spectrum to satisfy the requirements of human perception in some applications. In this paper, the evolution of active noise control and sound quality are briefly discussed. This paper emphasizes on the advancement of active noise control method in the past decades in terms of enhancing the sound quality

    Sparse complex FxLMS for active noise cancellation over spatial regions

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    In this paper, we investigate active noise control over large 2D spatial regions when the noise source is sparsely distributed. The l1 relaxation technique originated from compressive sensing is adopted and based on that we develop the algorithm for two cases: multipoint noise cancellation and wave domain noise cancellation. This results in two new variants (i) zero-attracting multi-point complex FxLMS and (ii) zero-attracting wave domain complex FxLMS. Both approaches use a feedback control system, where a microphone array is distributed over the boundary of the control region to measure the residual noise signals and a loudspeaker array is placed outside the microphone array to generate the anti-noise signals. Simulation results demonstrate the performance and advantages of the proposed methods in terms of convergence rate and spatial noise reduction levels.This work is supported by Australian Research Council (ARC) Discovery Projects funding scheme (project no. DP140103412). The work of J. Zhang was sponsored by the China Scholarship Council with the Australian National University

    A New Variable Regularized Transform Domain NLMS Adaptive Filtering Algorithm-Acoustic Applications and Performance Analysis

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