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.

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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

When 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

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

In image processing, one of the important problems is edge-preserving smoothing in mixed noise environment such that both Gaussian noise and impulsive noise exist Recently, several types of the hybrid filter which is a kind of nonlinear filter have been proposed for this purpose In this paper, a technique for edge-preserving smoothing is developed by using median finite impulse response (FIR) neural hybrid filters This filter structure is represented by the cascade connection of median filter, FIR filter, and neural network In this structure, the section of a median filter selects the median value among 3 points and the section of an FIR filter calculates the mean value of 3 points The section of neural network consists of three layered structure and its inputs equal the output from the section of a median filter and the output from the section of an FIR filter The major features of this filter are as follows: (1) This filter can adapt itself to the various noise environment through the learning of a training image (2) Even if a priori data such a training image is unavailable, this filter can efficiently be applied to edge-preserving smoothing for the images degraded by the Gaussian and impulsive noises Moreover, the structure of the proposed filter is very simple

Edge-preserving smoothing using median finite impulse response (FIR) hybrid filters

Mathematical morphology - fundamentals and advances

Among patients who visited our hospital with a chief complaint of disorders involving the oromandibular region, with suspected carotid artery calcification based on panoramic radiography, and who underwent computed tomography for a detailed examination of these disorders, there were four patients in whom a definitive diagnosis of carotid artery calcification was made. We herein provide an overview of these cases, along with a brief review of the relevant literature. When imaging findings suggestive of carotid artery calcification are obtained on panoramic radiographs, dentists can request detailed examinations and treatment at specialized medical institutions in the early stage by providing patients with information about the risks of atherosclerotic diseases. Early detection and treatment may reduce the severity or risks of complications and damage caused by atherosclerotic diseases, as well as possibly contributing to improved quality of life. In this study, we evaluated carotid artery calcification visible on panoramic radiographs. However, it seems that further detailed analysis is needed to examine the association between carotid artery calcification and a past history of risk factors for arteriosclerosis.

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Clinical Significance of Carotid Artery Calcification seen on Panoramic Radiographs

In this paper, we propose a sound field creation system based on the simultaneous equations method used for active noise control systems. Conventional studies on such sound field creation mainly focus on the transaural system reproducing recorded signals at the listening points. We differently purpose a system that creates the same sound field as that of a target. In the proposed system, inverse filters forming the target sound field are derived by using the simultaneous equations method, which is characterized by the use of auxiliary filters in estimating the error between the created and the target sounds. The auxiliary filters can also be used for detecting the deficiency in the number of taps of the inverse filters and in the delays to be added to the target sound field. The latter not only increases the error but also generates echoes preceding the created sound, which is annoying to listeners. In this paper, we finally verify the performance of the proposed system and also that the insufficiency can be detected by monitoring the coefficients of the auxiliary filter, by computer simulations.

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Mitsuji Muneyasu

Papers

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

Edge-preserving smoothing using median finite impulse response (FIR) hybrid filters

Mathematical morphology - fundamentals and advances

Clinical Significance of Carotid Artery Calcification seen on Panoramic Radiographs

Application of simultaneous equations method to sound field creation system