The problem of acoustic noise is becoming increasingly serious with the growing use of industrial and medical equipment, appliances, and consumer electronics. Active noise control (ANC), based on the principle of superposition, was developed in the early 20th century to help reduce noise. However, ANC is still not widely used owing to the effectiveness of control algorithms, and to the physical and economical constraints of practical applications. In this paper, we briefly introduce some fundamental ANC algorithms and theoretical analyses, and focus on recent advances on signal processing algorithms, implementation techniques, challenges for innovative applications, and open issues for further research and development of ANC systems.

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Recent Advances on Active Noise Control: Open Issues and Innovative Applications

FIRE operators for image processing

We propose a new edge enhancer based on a modified multilayer neural network, which is called a neural edge enhancer (NEE), for enhancing the desired edges clearly from noisy images. The NEE is a supervised edge enhancer: Through training with a set of input noisy images and teaching edges, the NEE acquires the function of a desired edge enhancer. The input images are synthesized from noiseless images by addition of noise. The teaching edges are made from the noiseless images by performing the desired edge enhancer. To investigate the performance, we carried out experiments to enhance edges from noisy artificial and natural images. By comparison with conventional edge enhancers, the following was demonstrated: The NEE was robust against noise, was able to enhance continuous edges from noisy images, and was superior to the conventional edge enhancers in similarity to the desired edges. To gain insight into the nonlinear kernel of the NEE, we performed analyses on the trained NEE. The results suggested that the trained NEE acquired directional gradient operators with smoothing. Furthermore, we propose a method for edge localization for the NEE. We compared the NEE, together with the proposed edge localization method, with a leading edge detector. The NEE was proven to be useful for enhancing edges from noisy images.

/pdf/neural-edge-enhancer-for-supervised-edge-enhancement-from-1n8x1nx2jy.pdf

Neural edge enhancer for supervised edge enhancement from noisy images

Active noise control (ANC) has been widely applied in industry to reduce environmental noise and equipment vibrations. Most available control algorithms require the identification of the secondary path, which increases the control system complexity, contributes to an increased residual noise power, and can even cause the control system to fail if the identified secondary path is not sufficiently close to the actual path. In this paper, based on the geometric analysis and the strict positive real (SPR) property of the filtered-x LMS algorithm, we introduce a new ANC algorithm suitable for single-tone noises as well as some specific narrowband noises that does not require the identification of the secondary path, though its convergence can be very slow in some special cases. We are able to extend the developed ANC algorithm to the case of active control of broadband noises through our use of a subband implementation of the ANC algorithm. Compared to other available control algorithms that do not require secondary path identification, our developed method is simple to implement, yields good performance, and converges quickly. Simulation results confirm the effectiveness of our proposed algorithm

A New Active Noise Control Algorithm That Requires No Secondary Path Identification Based on the SPR Property

The paper developed a reasonable and practical method for identifying the useful information from the signal that has been contaminated by noise, so that to provide a feasible tool for vibration analysis. A new concept namely the Singular Entropy (SE) was proposed based on the singular value decomposition technique. With the aid of the SE, a series of investigations were done for discovering the distribution characteristics of noise contaminated and pure signals, and consequently an advanced noise reduction method was developed. The experiments showed that the proposed method was not only applied for dealing with the stationary signals but also applied for dealing with the non-stationary signals.

https://msvlab.hre.ntou.edu.tw/NDT-Yang-2003.pdf

Development of an advanced noise reduction method for vibration analysis based on singular value decomposition

This paper proposes a step size control method capable of steadily canceling acoustic echo resisting double talk. The method is characterized by applying a sub-adaptive filter to the control. The step size and the number of taps of the sub- adaptive filter are larger and fewer than those of the main adaptive filter used for canceling the acoustic echo, respectively. Accordingly, the sub-adaptive filter can reduce the residual echo more rapidly than the main adaptive filter. The proposed method applies the step size calculated using the residual echo to the main adaptive filter, and thereby, quickly and steadily reduces the acoustic echo. This paper finally verifies that the proposed method can provide almost the same convergence speed as that obtained by applying a fixed large step size to the main adaptive filter.

Acoustic Echo Cancellation Algorithm Tolerable for Double Talk

This paper proposes a step size control method capable of steadily canceling acoustic echo even during double talk. The method is characterized by applying a sub-adaptive filter to the control. The step size and the number of taps of the sub-adaptive filter are larger and fewer than those of the main adaptive filter used for canceling the acoustic echo, respectively. Accordingly, the sub-adaptive filter can reduce the residual echo more rapidly than the main adaptive filter. The proposed method applies the step size calculated using the residual echo to the main adaptive filter, and thereby, quickly and steadily reduces the acoustic echo. This paper finally verifies that the proposed method can provide almost the same convergence speed as that obtained by applying an optimum step size to the main adaptive filter.

A step size control method steadily reducing acoustic echo even during double-talk

This paper considers a simple two-dimensional (2-D) IIR filter based on the Fornasini-Marchesini local state-space (LSS) model. It is shown that if image processing is carried out using such filters from four directions, smoothing, edge detection or edge enhancement can be achieved without any distortion. The proposed technique allows one to flexibly perform the forementioned filtering by choosing three parameters. Moreover, filter analysis including stability is easy due to using a well-known 2-D LSS model. Finally, some examples are given to illustrate the utility of the proposed technique.

Image processing by two-dimensional recursive filters using the fornasini-marchesini model

A computationally efficient technique is developed for the design of two- dimensional (2-D) recursive digital filters that meet simultaneously magnitude and phase specifications. A quadrantal symmetry which exists in the 2-D frequency response is incorporated into the 2-D filter design. The denominator and the numerator of a 2-D transfer function are designed individually: the former is used to approximate the constant group delays and then the latter is used to approximate the overall magnitude response. The filter design is analytically feasible by solving linear equations only. These serve to reduce the amount of calculations drastically. The stability of the resulting filters is always guaranteed. Finally two examples are given to illustrate the utility of the proposed technique.

Design of 2-D IIR digital filters with symmetry and constant group delays

The data hiding smart pair toggling (DHSPT) technique is one of watermarking techniques for grayscale halftone images This paper proposes an extension of DHSPT to color images and its improvement technique of watermarked halftone image quality by considering luminance components Simulation examples show the good image quality of the proposed technique

Mitsuji Muneyasu

Papers

Acoustic Echo Cancellation Algorithm Tolerable for Double Talk

A step size control method steadily reducing acoustic echo even during double-talk

Image processing by two-dimensional recursive filters using the fornasini-marchesini model

Design of 2-D IIR digital filters with symmetry and constant group delays

An extension of DHSPT to color half-tone images