Noise Control Filter Research Articles

A novel bilinear functional link neural network filter for nonlinear active noise control

The actual active noise control (ANC) systems often exist some nonlinearity in such cases: (1) the reference signals are chaotic noise; (2) the primary path is nonlinear; (3) the secondary path is nonlinear or non-minimum phase. To solve these problems, the well-known functional link neural network (FLNN) filter using trigonometric expansions is applied successfully in nonlinear ANC (NANC) systems. However, the FLNN filter still has some limitations, for example it does not have the ability to solve the problems of cross terms and acoustical feedback. For modifying the performance of FLNN filter, we propose a new bilinear FLNN (BFLNN) filter combining the trigonometric function expansion, feedback output signals and the products of input signals and feedback output signals. The proposed BFLNN filter is based on a recursive structure which can represent the real nonlinear systems with fewer coefficients than non-recursive models do. Moreover, to some extent the recursive structure can compensate the acoustical feedback between reference microphone and secondary speaker. However, considering the stability of the recursive structure, this paper also offers a sufficient stability condition for the proposed BFLNN filter. Through analysis, the products of input signals and output signals can provide more comprehensive expression for the cross-term problem. To demonstrate the effectiveness of the proposed BFLNN filter, numerous simulation studies considering the problems of cross terms and acoustical feedback in the presence of different reference signals and acoustic paths are conducted in simulation section, and the results prove that the proposed BFLNN filter is more suitable for NANC systems.

A robust approach for online feedback path modeling in single-channel narrow-band active noise control systems using two distinct variable step size methods

Online feedback path modeling and neutralization (FBPMN) is vital in active noise control (ANC) systems to ensure stability and elevate performance in non-stationary environments. In this paper, we propose a modified variable step size (VSS) method for online FBPMN in single-channel ANC systems which incorporates three adaptive filters; a noise control filter, a FBPMN filter, and a linear predictor for disturbance removal. In the proposed method, distinct VSS LMS algorithms are used for FBPMN filter and disturbance removal filter to achieve exceptionally fast convergence and accurate modeling of the feedback path transfer function. Simulation results show that the proposed method yields a significantly more robust ANC system by attaining a higher gain margin at a much faster rate in comparison with the existing methods.

A bilinear functional link artificial neural network filter for nonlinear active noise control and its stability condition

Since the functional link artificial neural network (FLANN) filter using trigonometric expansions do not exploit cross-terms (products of input samples and /or past output samples with different time shifts), its performance for nonlinear active noise control (ANC) can be considerably degraded, especially in strong nonlinearity environment. In order to overcome this drawback, a novel bilinear FLANN (BFLANN) filter for the nonlinear ANC is proposed in this paper. In addition, a sufficient condition that guarantees the stability of the BFLANN filter is also presented. Simulation results demonstrate that the proposed BFLANN filter based nonlinear ANC can achieve better performance than the FLANN and generalized FLANN (GFLANN) filters based nonlinear ANC in the presence of strong nonlinearity.

Gain Scheduling of Auxiliary Noise and Variable Step-Size for Online Acoustic Feedback Cancellation in Narrow-Band Active Noise Control Systems

In this paper, we investigate active noise control systems, which use auxiliary white Gaussian noise for online feedback path modeling and neutralization. Such systems comprise three adaptive filters: 1) active noise control filter, 2) linear prediction filter, and 3) feedback path modeling and neutralization filter. The injection of white Gaussian noise with large/small variance improves/degrades the convergence of feedback path modeling and neutralization filter but on the other hand degrades/improves the noise-reduction performance of active noise control systems. The focus of this paper is to have an adequate compromise between the convergence of feedback path modeling and neutralization filter and the noise-reduction-performance of active noise control systems. In this paper: 1) A tuning free gain scheduling of white Gaussian noise is used to improve the noise-reduction performance of active noise control systems, and 2) a variable step-size is used to compensate for the decrease in the convergence of feedback path modeling and neutralization filter due to gain scheduling. The proposed idea is explained for a single channel as well as for multichannel active noise control systems. Computer simulations have been carried out to demonstrate the performance of the proposed method for a single channel as well as for multichannel active noise control systems.

A numerically stable, finite memory, fast array recursive least squares filter for broadband active noise control

SummaryFor broadband active noise control applications with a rapidly changing primary path, it is desirable to find algorithms with a rapid convergence, a fast tracking performance, and a low computational cost. Recently, a promising algorithm has been presented, called the fast‐array Kalman filter, which uses rotation matrices to calculate the filter parameters. However, when this algorithm is implemented, it can show unstable behavior because of finite precision error propagation. In this paper, a novel algorithm is presented, which exhibits the fast convergence and tracking properties and the linear calculation complexity of the fast‐array Kalman filter but does not suffer from the mentioned numerical problems. This is accomplished by running two finite length growing memory recursive least squares filters in parallel and using a convex combination of the two filters when the control signal is calculated. A reset of the filter parameters with proper re‐initialization is enforced periodically. The mixing parameters will be chosen in such a way that the total available information used for the calculation of the control signal will be approximately equal at every time instance. The performance of the filter is shown in numerical simulations and real‐time lab experiments. The numerical experiments show that the algorithm performs better numerically than the fast‐array sliding window recursive least squares filter, while achieving a comparable convergence rate and tracking performance. The real‐time lab experiments confirm the behavior shown in the simulations. Copyright © 2015 John Wiley & Sons, Ltd.

퍼지논리 안정화알고리즘을 이용한 다중채널 능동소음제어시스템

능동 소음제어 시스템에 사용되는 IIR 필터 구조는 구조적으로 안정성이 보장되어야 하며 이는 분모 전달 함수의 근이 단위원 내부에 존재하여야 한다. 따라서 이를 결정하는 제어 필터의 계수의 적절한 조정이 중요해 진다. 본 논문에서는 적응과정에서 불안정할 우려가 있는 IIR 필터 구조를 가지는 Filtered_U LMS 알고리즘에 안정화 알고리즘과 수렴속도 향상을 위한 퍼지논리를 이용한 수렴계수 계산 알고리즘을 제안하였다. 제안한 알고리즘이 FIR 필터 구조 알고리즘보다 계산량이 적고 수렴특성이 우수함을 시뮬레이션을 통하여 보였다. In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

Application of Simultaneous Equations Method to ANC System with Non-minimum Phase Secondary Path

In this paper, we propose a method capable of shortening the distance from a noise detection microphone to a loudspeaker in active noise control system with non-minimum phase secondary path. The distance can be basically shortened by forming the noise control filter, which produces the secondary noise provided by the loudspeaker, with the cascade connection of a non-recursive filter and a recursive filter. The output of the recursive filter, however, diverges even when the secondary path includes only a minimum phase component. In this paper, we prevent the divergence by utilizing MINT (multi-input/output inverse theorem) method increasing the number of secondary paths than that of primary paths. MINT method, however, requires a large scale inverse matrix operation, which increases the processing cost. We hence propose a method reducing the processing cost. Actually, MINT method has only to be applied to the non-minimum phase components of the secondary paths. We hence extract the non-minimum phase components and then apply MINT method only to those. The order of the inverse matrix thereby decreases and the processing cost can be reduced. We finally show a simulation result demonstrating that the proposed method successfully works.

Multi-Channel Active Noise Control System Designs with Fuzzy Logic Stabilized Algorithms

In active noise control filter, IIR filter structure which used for control filter assures the stability property. The stability characteristics of IIR filter structure is mainly determined by pole location of control filter within unit disc, so stable selection of the value of control filter coefficient is very important. In this paper, we proposed novel adaptive stabilized Filtered_U LMS algorithms with IIR filter structure which has better convergence speed and less computational burden than conventional FIR structures, for multi-channel active noise control with vehicle enclosure signal case. For better convergence speed in adaptive algorithms, fuzzy LMS algorithms where convergence coefficient computed by a fuzzy PI type controller was proposed.

Acoustical design of heathcare facilities for leadership in energy and environmental design green building certification: Odd harmonic filter for mechanical system noise control.

To achieve the leadership in energy and environmental design (LEED) indoor environmental quality credit 2: acoustic environment, healthcare facilities must meet stringent sound and vibration criteria. Mechanical system noise presents one of the largest obstacles to meeting the room noise design requirements. Code requirements intended to promote indoor air quality, and infection control limits the use of typical absorptive materials such as fiberglass duct liner, packed duct silencers, and other porous absorbers. Energy code requirements force mechanical system designers to locate large noise sources such as air handlers, fan‐powered terminal air boxes, and exhaust fans close to the spaces they serve, adding to background noise levels. One innovative, practical solution to tonal mechanical system noise is an odd harmonic filter. Acoustical performance of odd harmonic filters and strategies to achieve the room noise criteria for the LEED acoustic environment credit will be discussed.

Application of Cascade Connection of Recursive and Non-recursive Filters to Active Noise Control System Using Simultaneous Equations Method

In this paper, we propose a method capable of shortening the distance from a noise detection microphone to a loudspeaker, which is one of important issues in the field of active noise control (ANC). In the ANC system, the secondary noise provided by the loudspeaker is required arriving at an error microphone simultaneously with the primary noise to be cancelled. However, the reverberation involved in the secondary path from the loudspeaker to the error microphone increases the secondary noise components arriving later than the primary noise. The late components are not only invalid for canceling the primary noise but also impede the cancellation. To reduce the late components, the distance between the noise detection microphone and the loud speaker is generally extended. The proposed method differently reduces the late components by forming the noise control filter, which produces the secondary noise, with the cascade connection of a non-recursive and a recursive filters. The distance can be thus shortened. On the other hand, the recursive filter is required to work stably. The proposed method guarantees the stable work by forming the recursive filter with the lattice filter whose coefficients are restricted to less than unity.

Ultra-wide-band filter for noise control.

Extensive band structures are performed for two-dimensional periodic arrays of rigid stainless steel cylinders in air, with Bloch vector being perpendicular to the cylinders. We embark on the opening up of a complete acoustic band gap—independent of the polarization of the wave and of the direction of propagation. In addition, we propose the fabrication of a multiperiodic system in tandem that could create a huge hole in sound within the human audible range of frequencies.

On Active Noise Control Systems With Online Acoustic Feedback Path Modeling

The presence of strong acoustic feedback degrades the convergence speed of the active noise control (ANC) filter, and in the worst case the ANC system may become unstable. A fixed feedback neutralization filter, obtained offline, can be used to neutralize the acoustic feedback. The feedback path, however, may be time varying, and we may need continual adjustments during online operation of the ANC system. This paper proposes a new method for online modeling of the acoustic feedback path in ANC systems. The proposed method uses three adaptive filters; a noise control filter, a feedback path modeling (FBPM) filter, and an adaptive noise cancelation (ADNC) filter. The objective of ADNC filter is to remove the disturbance from the desired response of FBPM filter. In comparison with the existing method, which works only for predictable noise sources, the proposed method can work, as well, with the broadband noise sources. The computer simulations are carried out for narrowband (predictable) (case I) and broadband (random) noise sources (case II). It is demonstrated that the proposed method performs better than the existing method in both cases

Frequency domain simultaneous equations method for active noise control systems

This study proposes a new method for feedforward‐type active noise control systems. This method, named the frequency domain simultaneous equations method, is based on a different principle from the filtered‐x algorithm requiring a filter modeled on a secondary path from a loudspeaker to an error microphone. Instead of the filter, this method uses an auxiliary filter identifying the overall path consisting of a primary path, a noise control filter, and the secondary path. As seen from the configuration of the overall path, the auxiliary filter can provide two independent equations when two different coefficient vectors are given to the noise control filter. In practical use, the two different coefficient vectors are provided by their own estimation errors. By solving the independent equations, the proposed method can estimate the coefficient vector of the noise control filter minimizing the output of the error microphone. This study first presents computer simulation results demonstrating that the proposed method can automatically recover the noise reduction that is in effect degraded by path changes. Finally, this study applies the proposed method to an experimental system and, by using the system, verifies that the proposed method is functional in practical systems.

A frequency domain method to estimate the coefficients of feedback control filter

This study proposes a method for repeatedly updating coefficients of a feedback control filter used for canceling a feedback path from a loudspeaker to a noise detection microphone. The coefficients are typically estimated by feeding a sequence of extra noise to the loudspeaker. However, feeding such extra noise under active noise control is undesirable. The proposed method estimates the coefficients without feeding the extra noise. Using the estimation errors involved in the coefficients of the noise control filter instead of the extra noise, the proposed method provides two independent equations and estimates coefficients of the feedback control filter by solving those. The two independent equations are provided through linear prediction using an auxiliary filter. A solution of the equations with two unknowns (a primary noise and the feedback path) provides the coefficients of the feedback control filter, perfectly canceling the feedback path. A salient drawback is that the feedback component is extremely small in comparison to the primary noise that is incident on the noise detection microphone. For that reason, estimation of the coefficients is difficult. This method solves the problem by first estimating the primary noise and then the feedback path.

An Active Noise Control System Based on Simultaneous Equations Method without Auxiliary Filters

A simultaneous equations method is one of active noise control algorithms without estimating an error path. This algorithm requires identification of a transfer function from a reference microphone to an error microphone containing the effect of a noise control filter. It is achieved by system identification of an auxiliary filter. However, the introduction of the auxiliary filter requires more number of samples to obtain the noise control filter and brings a requirement of some undesirable assumption in the multiple channel case. In this paper, a new simultaneous equations method without the identification of the auxiliary filter is proposed. By storing a small number of input signals and error signals, we avoid this identification. Therefore, we can reduce the number of samples to obtain the noise control filters and can avoid the undesirable assumption. From simulation examples, it is verified that the merits of the ordinary method is also retained in the proposed method.

A new variable step size LMS algorithm-based method for improved online secondary path modeling in active noise control systems

This paper proposes a new method for online secondary path modeling in active noise control systems. The existing methods for active noise control systems with online secondary path modeling consist of three adaptive filters. The main feature of the proposed method is that it uses only two adaptive filters. In the proposed method, the modified-FxLMS (MFxLMS) algorithm is used in adapting the noise control filter and a new variable step size (VSS) least mean square (LMS) algorithm is proposed for adaptation of the secondary path modeling filter. This VSS LMS algorithm is different from the normalized-LMS (NLMS) algorithm, where the step size is varied in accordance with the power of the reference signal. Here, on the other hand, the step size is varied in accordance with the power of the disturbance signal in the desired response of the modeling filter. The basic idea of the proposed VSS algorithm stems from the fact that the disturbance signal in the desired response of the modeling filter is decreasing in nature, (ideally) converging to zero. Hence, a small step size is used initially and later its value is increased accordingly. The disturbance signal, however, is not available directly, and we propose an indirect method to track its variations. Computer simulations show that the proposed method gives better performance than the existing methods. This improved performance is achieved at the cost of a slightly increased computational complexity.

Verification of simultaneous equations method by an experimental active noise control system

In this study, we verify the performance of the simultaneous equations method using an experimental active noise control system. The simultaneous equations method is based on a priciple different from the filtered-x algorithm requiring a filter modeled on a secondary path from a loudspeaker to an error microphone. Instead of the filter, called the secondary path filter, this method uses an auxiliary filter identifying the overall path consisting of a primary path, a noise control filter and the secondary path. As inferred from the configuration of the overall path, the auxiliary filter can provide two independent equations when two different coefficient vectors are given to the noise control filter. The method thereby estimates the coefficient vector of the noise control filter minimizing the output of the error microphone. In this paper, we propose the application of a frequency domain adaptive algorithm to the identification of the overall path. An improvement in the noise reduction speed is thereby expected. In this paper, we also present computer simulation results demonstrating that the simultaneous equations method can automatically recover the noise reduction effect degraded by path changes, and finally, using an experimental system, we indicate that the method successfully works in practical systems.

Frequency domain method to estimate the coefficients of feedback control filter for active noise control systems

In this paper, we propose a method for repeatedly updating the coefficients of the feedback control filter used for canceling a feedback path from a loudspeaker to a noise detection microphone. The coefficients are usually estimated by feeding a sequence of extra noise to the loudspeaker. However, feeding such extra noise under active noise control is undesirable. The proposed method estimates the coefficients without feeding the extra noise. Concretely the proposed method provides two independent equations using the estimation errors involved in the coefficients of the noise control filter and then estimates the coefficients by solving those equations. One problem is that the feedback component is extremely small in comparison with the primary noise incident on the noise detection microphone. In this case, estimation of the coefficients is difficult. In this work. we solves this problem by estimating first the primary noise and then the feedback path.

Active noise control system using the simultaneous equation method without the estimation of error path filter coefficients

AbstractIn an active noise control system that uses the Filtered‐x method as an adaptive algorithm, the impulse response on the error path is observed and the result is assigned as a coefficient of an error path filter before the system is started. Such an impulse response can obviously change after the system is started. The change can increase the difference between the assigned coefficient and the inherent coefficient of the error path filter, and thus render the operation of noise control unstable. This paper proposes a noise control filter coefficient renewal method that does not require the calculation of an error path filter coefficient by focusing on the fact that, when a set of two different coefficients is assigned to a noise control filter, the system consisting of components from a noise detection microphone to an error detection microphone establishes two independent equations whose variables are impulse responses for the feedforward path and the error path system. The coefficient of the noise control filer can be renewed by solving the simultaneous equations by iteration. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 3, 85(12): 101–108, 2002; Published online in Wiley InterScience (www.interscience.wiley. com). DOI 10.1002/ecjc.1132

An extension of simultaneous equation method to multiple channel active noise control system

AbstractWhen a region with a certain area needs silencing, no sufficient effect can be obtained with a single‐channel active noise control system. Therefore, multiple channel noise control systems using several microphones and speakers have been proposed. One of the algorithms used frequently is the Multiple Error Filtered‐X (MEFX) method. The MEFX method requires prior estimation of the error path system. In the case of multiple channels, the estimation error poses more complex effects in comparison to the single channel. In addition, variations of the system during operation are problematic. In this paper, the simultaneous equation method recently proposed for the single channel in which no estimation is required for the error path system is applied to the multiple channel active noise control. In the present procedure, the coefficients of the noise control filter can be estimated without estimation of the error path system as in the case of the single channel. The method can handle the variation of the path during operation and can obtain excellent silencing effects. © 2002 Scripta Technica, Electron Comm Jpn Pt 3, 85(5): 46–55, 2002