5,476 research outputs found
Adaptive multichannel control of time-varying broadband noise and vibrations
This paper presents results obtained from a number of applications in which a recent adaptive algorithm for broadband multichannel active noise control is used. The core of the algorithm uses the inverse of the minimum-phase part of the secondary path for improvement of the speed of convergence. A further improvement of the speed of convergence is obtained by using double control filters for elimination of adaptation loop delay. Regularization was found to be necessary for robust operation. The regularization technique which is used preserves the structure to eliminate the adaptation loop delay. Depending on the application at hand, a number of extensions are used for this algorithm. For an application with rapidly changing disturbance spectra, the core algorithm was extended with an iterative affine projection scheme, leading to improved convergence rates as compared to the standard nomalized lms update rules. In another application, in which the influence of the parametric uncertainties was critical, the core algorithm was extended with low authority control loops operating at high sample rates. In addition, results of other applications are given, such as control of acoustic energy density and control of time-varying periodic and non-periodic vibrations
Rapidly converging multichannel controllers for broadband noise and vibrations
Applications are given of a preconditioned adaptive algorithm for broadband multichannel active noise control. Based on state-space descriptions of the relevant transfer functions, the algorithm uses the inverse of the minimum-phase part of the secondary path in order to improve the speed of convergence. A further improvement of the convergence rate is obtained by using double control filters for elimination of adaptation loop delay. Regularization was found to be essential for robust operation. The particular regularization technique preserves the structure to eliminate the adaptation loop delay. Depending on the application at hand, a number of extensions are used for this algorithm, such as for applications with rapidly changing disturbance spectra, applications with large parametric uncertainty, applications with control of time-varying acoustic energy density
Active control of sound inside a sphere via control of the acoustic pressure at the boundary surface
Here we investigate the practical feasibility of performing soundfield
reproduction throughout a three-dimensional area by controlling the acoustic
pressure measured at the boundary surface of the volume in question. The main
aim is to obtain quantitative data showing what performances a practical
implementation of this strategy is likely to yield. In particular, the
influence of two main limitations is studied, namely the spatial aliasing and
the resonance problems occurring at the eigenfrequencies associated with the
internal Dirichlet problem. The strategy studied is first approached by
performing numerical simulations, and then in experiments involving active
noise cancellation inside a sphere in an anechoic environment. The results show
that noise can be efficiently cancelled everywhere inside the sphere in a wide
frequency range, in the case of both pure tones and broadband noise, including
cases where the wavelength is similar to the diameter of the sphere. Excellent
agreement was observed between the results of the simulations and the
measurements. This method can be expected to yield similar performances when it
is used to reproduce soundfields.Comment: 28 pages de text
An investigation of delayless subband adaptive filtering for multi-input multi-output active noise control applications
The broadband control of noise and vibration using multi-input, multi-output (MIMO) active control systems has a potentially wide variety of applications. However, the performance of MIMO systems is often limited in practice by high computational demand and slow convergence speeds. In the somewhat simpler context of single-input, single- output broadband control, these problems have been overcome through a variety of methods including subband adaptive filtering. This paper presents an extension of the subband adaptive filtering technique to the MIMO active control problem and presents a comprehensive study of both the computational requirements and control performance. The implementation of the MIMO filtered-x LMS algorithm using subband adaptive filtering is described and the details of two specific implementations are presented. The computational demands of the two MIMO subband active control algorithms are then compared to that of the standard full-band algorithm. This comparison shows that as the number of subbands employed in the subband algorithms is increased, the computational demand is significantly reduced compared to the full-band implementation provided that a restructured analysis filter-bank is employed. An analysis of the convergence of the MIMO subband adaptive algorithm is then presented and this demonstrates that although the convergence of the control filter coefficients is dependent on the eigenvalue spread of the subband Hessian matrix, which reduces as the number of subbands is increased, the convergence of the cost function is limited for large numbers of subbands due to the simultaneous increase in the weight stacking distortion. The performance of the two MIMO subband algorithms and the standard full-band algorithm has then been assessed through a series of time-domain simulations of a practical active control system and it has been shown that the subband algorithms are able to achieve a significant increase in the convergence speed compared to the full-band implementatio
Infinite non-causality in active cancellation of random noise
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
Sunyaev-Zel'dovich clusters reconstruction in multiband bolometer camera surveys
We present a new method for the reconstruction of Sunyaev-Zel'dovich (SZ)
galaxy clusters in future SZ-survey experiments using multiband bolometer
cameras such as Olimpo, APEX, or Planck. Our goal is to optimise SZ-Cluster
extraction from our observed noisy maps. We wish to emphasize that none of the
algorithms used in the detection chain is tuned on prior knowledge on the SZ
-Cluster signal, or other astrophysical sources (Optical Spectrum, Noise
Covariance Matrix, or covariance of SZ Cluster wavelet coefficients). First, a
blind separation of the different astrophysical components which contribute to
the observations is conducted using an Independent Component Analysis (ICA)
method. Then, a recent non linear filtering technique in the wavelet domain,
based on multiscale entropy and the False Discovery Rate (FDR) method, is used
to detect and reconstruct the galaxy clusters. Finally, we use the Source
Extractor software to identify the detected clusters. The proposed method was
applied on realistic simulations of observations. As for global detection
efficiency, this new method is impressive as it provides comparable results to
Pierpaoli et al. method being however a blind algorithm. Preprint with full
resolution figures is available at the URL:
w10-dapnia.saclay.cea.fr/Phocea/Vie_des_labos/Ast/ast_visu.php?id_ast=728Comment: Submitted to A&A. 32 Pages, text onl
Adaptive Filtered-x Algorithms for Room Equalization Based on Block-Based Combination Schemes
(c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.[EN] Room equalization has become essential for sound reproduction systems to provide the listener with the desired acoustical sensation. Recently, adaptive filters have been proposed as an effective tool in the core of these systems. In this context, this paper introduces different novel schemes based on the combination of adaptive filters idea: a versatile and flexible approach that permits obtaining adaptive schemes combining the capabilities of several independent adaptive filters. In this way, we have investigated the advantages of a scheme called combination of block-based adaptive filters which allows a blockwise combination splitting the adaptive filters into nonoverlapping blocks. This idea was previously applied to the plant identification problem, but has to be properly modified to obtain a suitable behavior in the equalization application. Moreover, we propose a scheme with the aim of further improving the equalization performance using the a priori knowledge of the energy distribution of the optimal inverse filter, where the block filters are chosen to fit with the coefficients energy distribution. Furthermore, the biased block-based filter is also introduced as a particular case of the combination scheme, especially suited for low signal-to-noise ratios (SNRs) or sparse scenarios. Although the combined schemes can be employed with any kind of adaptive filter, we employ the filtered-x improved proportionate normalized least mean square algorithm as basis of the proposed algorithms, allowing to introduce a novel combination scheme based on partitioned block schemes where different blocks of the adaptive filter use different parameter settings. Several experiments are included to evaluate the proposed algorithms in terms of convergence speed and steady-state behavior for different degrees of sparseness and SNRs.The work of L. A. Azpicueta-Ruiz was supported in part by the Comtmidad de Madrid through CASI-CAM-CM under Grant S2013/ICE-2845, in part by the Spanish Ministry of Economy and Competitiveness through DAMA under Grant TIN2015-70308-REDT, and Grant TEC2014-52289-R, and in part by the European Union. The work of L. Fuster, M. Ferrer, and M. de Diego was supported in part by EU together with the Spanish Government under Grant TEC2015-67387-C4-1-R (MINECO/FEDER), and in part by the Cieneralitat Valenciana under Grant PROMETEOII/2014/003. The associate editor coordinating the review of this manuscript and approving it for publication was Prof. Simon Dodo.Fuster Criado, L.; Diego Antón, MD.; Azpicueta-Ruiz, LA.; Ferrer Contreras, M. (2016). Adaptive Filtered-x Algorithms for Room Equalization Based on Block-Based Combination Schemes. IEEE/ACM Transactions on Audio, Speech and Language Processing. 24(10):1732-1745. https://doi.org/10.1109/TASLP.2016.2583065S17321745241
Combined MIMO adaptive and decentralized controllers for broadband active noise and vibration control
Recent implementations of multiple-input multiple-output adaptive controllers for reduction of broadband noise and vibrations provide considerably improved performance over traditional adaptive algorithms. The most significant performance improvements are in terms of speed of convergence, the \ud
amount of reduction, and stability of the algorithm. Nevertheless, if the error in the model of the relevant transfer functions becomes too large then the system may become unstable or lose performance. On-line adaptation of the model is possible in principle but, for rapid changes in the model, necessitates \ud
a large amount of additional noise to be injected in the system. It has been known for decades that a combination of high-authority control (HAC) and low-authority control (LAC) could lead to improvements with respect to parametric uncertainties and unmodeled dynamics. In this paper a full digital implementation of such a control system is presented in which the HAC (adaptive MIMO control) is implemented on a CPU and in which the LAC (decentralized control) is implemented on a high-speed Field Programmable Gate Array. Experimental results are given in which it is demonstrated that the HAC/LAC combination leads to performance advantages in terms of stabilization under parametric uncertainties and reduction of the error signal
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