Noise Cancellation Technology Research Articles

Bluetooth Active Noise Cancellation (ANC) Technology: Principles, Integration, Applications, and Performance Evaluation

Thanks to the development of wireless audio transmission technology, Bluetooth technology made it possible to give users a seamless and convenient connection experience. However, in a noisy environment, preserving the audio quality is still difficult, which motivated people to explore the technology of Active Noise Cancellation (ANC). This paper aims to analyze integration of ANC technology and the potential of Bluetooth audio transmitting to improve the audio effect, especially in application scenarios where clear audio is required. At the beginning of this paper, how Bluetooth and ANC are evolved is reviewed for the preparatory works. Then, the technology mechanism of the ANC and the advantages in particular application scenarios such as Industrial automation and autonomous vehicles are described in detail. In addition, this paper give experimental data to illustrate that the ANC systems is effective in reducing ambient noise. The central technology of ANC system is using a microphone to detect environmental noise information and then creates a sound wave phase-inverted to the original noise to cancel. Furthermore, by connecting artificial intelligence technique, the ANC system dynamically fits from different acoustic environment to improve the audio quality. Finally, the experimental results that are quoted reveal that the advanced ANC system can reduce the noise level in a wide range of environments, cutting down the sound pressure level to 65 dB. It is clearly demonstrated that the ANC technology is widely applicable and effective to enhance the audio experience.

EXPLORING THE CONCEPT OF AMBIENT SOUND FOR WELL-BEING: A SYSTEMATIC REVIEW OF THEORIES AND EVIDENCEON

This study investigates the impact of ambient sound on well-being, focusing on its definition, theoretical foundations, and cultural interpretations. The objectives are to explore and analyse underlying theories and concepts, and to examine cultural perceptions of ambient sound’s influence on human life. The researchers searched multiple databases, including JSTOR, PubMed, and Scopus, using keywords related to ambient sound and its synonyms. A total of 162 articles were examined and only 46 articles were included in the review. The results of this review proposed that definition of ambient sound highlights its role as the comprehensive auditory backdrop that shapes individuals’ perceptions, understanding, and experiences of a specific location, incorporating various elements such as natural sounds, background noises, and human-generated sounds. This definition underscores the significance of ambient sound in shaping the overall sonic atmosphere and cultural interpretation of a particular space. Additionally, the perception of environmental noise varies across cultures, and cultural factors influence the use and acceptance of noise cancellation technology and the significance attributed to natural sounds. Further research is needed to explore the potential benefit of ambient sound as a background sound within a various settings such as therapeutic environment.

IEC60270 규격에 따른 직류부분방전 측정 장치용 임펄스 잡음 제거 기술

IEC60270 규격에 따른 직류부분방전 측정 장치용 임펄스 잡음 제거 기술

Improved Phase Noise Cancellation Technology for Auxiliary Reference Interferometer Demodulation Scheme

In an unbalanced interferometer, the phase noise level is positively related to the optical path length difference (OPD) and the wavelength instability of the light source. The effective current solution for reducing phase noise is to use an auxiliary reference interferometer to measure the phase noise signal. However, this method requires that all interferometers have the same OPD, otherwise the phase modulation depth of different interferometers with the same light source will be different and the noise reduction effect will be severely reduced. It is difficult to provide interferometers with precisely the same OPD in practical. In this paper, an improved phase-generated carrier (PGC) demodulation technique for phase noise cancellation that does not require strictly equal OPDs of interferometers is proposed. Combining an auxiliary reference interferometer scheme with an ellipse fitting algorithm (EFA) can eliminate the effect of different phase modulation depths due to different OPDs, and phase modulation depth drift on demodulation results, significantly reducing harmonic distortion. The additional phase modulation signal ensures the correct calculation of small signals by the EFA, while the OPDs of the interferometers are evaluated in real time to achieve constant phase noise cancellation capability under different OPD. Experimental results show that the proposed technique achieves a highly stable phase demodulation result with a maximum phase noise reduction of about 9dB and a minimum THD of -74.59 dB in interferometers with non-strict equal OPD.

Evaluating the hearing screening effectiveness of active noise cancellation technology among young adults: A pilot study.

The population of young adults who are hearing impaired increases yearly, and a device that enables convenient hearing screening could help monitor their hearing. However, background noise is a critical issue that limits the capabilities of such a device. Therefore, this study evaluated the effectiveness of commercial active noise cancellation (ANC) headphones for hearing screening applications in the presence of background noise. In particular, six confounders were used for a comprehensive evaluation. We enrolled 12 young adults (a total of 23 ears with normal hearing) to participate in this study. A cross-sectional self-controlled study was conducted to explore the effectiveness of hearing screening in the presence of background noise, with a total of 240 test conditions (=3 ANC models × 2 ANC function statuses × 2 noise types × 5 noise levels × 4 frequencies) for each test ear. Subsequently, a linear regression model was used to prove the effectiveness of ANC headphones for hearing screening applications in the presence of background noise with six confounders. The experimental results showed that, on average, the ANC function of headphones can improve the effectiveness of hearing screening tasks in the presence of background noise. Specifically, the statistical analysis showed that the ANC function enabled a significant 10% improvement ( p < 0.001) compared with no ANC function. This study confirmed the effectiveness of ANC headphones for young adult hearing screening applications in the presence of background noise. Furthermore, the statistical results confirmed that as confounding variables, noise type, noise level, hearing screening frequency, ANC headphone model, and sex all affect the effectiveness of the ANC function. These findings suggest that ANC is a potential means of helping users obtain high-accuracy hearing screening results in the presence of background noise. Moreover, we present possible directions of development for ANC headphones in future studies.

Objective Signal Analysis for Investigating Feasibility of Active Noise Cancellation in Hearing Screening.

With the development of active noise cancellation (ANC) technology, ANC has been used to mitigate the effects of environmental noise on audiometric results. However, objective evaluation methods supporting the accuracy of audiometry for ANC exposure to different levels of noise have not been reported. Accordingly, the audio characteristics of three different ANC headphone models were quantified under different noise conditions and the feasibility of ANC in noisy environments was investigated. Steady (pink noise) and non-steady noise (cafeteria babble noise) were used to simulate noisy environments. We compared the integrity of pure-tone signals obtained from three different ANC headphone models after processing under different noise scenarios and analyzed the degree of ANC signal correlation based on the Pearson correlation coefficient compared to pure-tone signals in quiet. The objective signal correlation results were compared with audiometric screening results to confirm the correspondence. Results revealed that ANC helped mitigate the effects of environmental noise on the measured signal and the combined ANC headset model retained the highest signal integrity. The degree of signal correlation was used as a confidence indicator for the accuracy of hearing screening in noise results. It was found that the ANC technique can be further improved for more complex noisy environments.

Artificial intelligent techniques applied for detection COVID-19 based on chest medical imaging

One of the ways to detect coronavirus disease of 2019 (COVID-19) is X-rays, computerized tomography (CT). This paper aims to detect COVID-19 from CT images without any user intervention. The proposed algorithm consists of 5 stages. These stages include; the first stage aims to collect data from hospitals and internet websites, the second stage is pre-processing stage to remove noise and convert it from red green blue (RGB) to grayscale and then improve image quality, the third is the segmentation stage which included threshold and region-growing segmentation methods. The fourth stage is used to extract important characteristics, and the last stage is classification CT images using feed forward back propagation network (FFBPN) and support vector machines (SVM) and compare the results between them and see if the person is infected or healthy. This study was implemented in MATLAB software. The results showed that the noise cancellation technology using anisotropic filtering gave the best results. Region-growing method was reliable to separate COVID-19 infected from healthy regions. The FFBPN has given the best results for detecting and classifying COVID-19. The results of the proposed methodology are rapid and accurate in detecting COVID-19. The output from classifier is displayed on the Rasbperry Pi that included weather if patient is infected or not and the severity of COVID-19 infection.

Artificial Intelligent Techniques Applied for Detection Covid-19 Based on Chest Medical Imaging

One of the ways to detect COVID is x-rays, computerized tomography (CT). This paper aims to detect COVID-19 without any user intervention. The proposed algorithm consists of 5 stages to detect and classify COVID-19 from cross-sectional images. These stages include; The first of these stages is to collect data from hospitals as real data and from the Internet for the injured and other healthy people, then the pre-noise removal stage and convert it from RGB to grayscale, then we improve the image, segmentation and formalities, the other stage is a stage used to extract important characteristics, and the last stage is classification CT images using FFBPN and SVM and compare the result between them and see if the person is infected or healthy. This study was implemented in Matlab software. The results showed that the noise cancellation technology using anisotropic filtering gave the best results. As for the optimization technology, only the brightness of the images has been increased. At the stage of segmentation of the area of lung injection using the area transplant method, the best results are the detection of COVID-19 from other healthy tissues. The FFBPN has given the best results for detecting and classifying COVID-19 as well as determining whether a person has been infected or not. The results of the proposed methodology in accurate and rapid detection of COVID-19 in the lung.

Research on a cascade model synthesis with the use of classical and non-classical methods in the context of new piezoelectric stack applications

Abstract. Active audio noise cancellation technology using piezoelements is fairly new and emerging technology on the market in recent years and is still gaining in popularity. The ability to use piezoelectric devices to gather information about vibration spectrum and to create interfering waves, to cancel out the noise, allows for the reduction in passive vibration methods and gives more flexibility in terms of space and application. The idea of using this technique on larger scales such as industrial equipment is the focus of ongoing research conducted by the authors of this article. This work is intended as the first part of a larger project and focuses solely on theoretical approach to the problem of modelling mechatronic systems capable of creating complex vibration spectrums and using piezoelectric components. The authors have focused on creating a mix of classical and non-classical methods to synthesize model systems based on input resonance frequencies. A classical calculation through matrix equations was also done to validate the accuracy of obtained results through the structural number method. The resulting model is still awaiting the empirical verification through extensive testing on real-life models, and that part of the research is still being developed. When validated and checked, this technology could bring new solutions in the vibration damping of industrial equipment, potentially increasing its flexibility and effectiveness.

Detection of COVID-19 Based on Chest Medical Imaging and Artificial Intelligence Techniques

The emergence of COVID-19 disease in the world has moved the wheel of scientific research in order to detect it in the best method, and the fastest of these methods is the use of Artificial Intelligence (AI) techniques to help medical professionals detect COVID-19. The proposed topic is aim to develop algorithm based on combination between imageprocessing techniques with artificial intelligence to diagnose COVID-19. The proposed algorithm consists of five stages to detect and classify COVID-19 from Computer Tomography (CT) images. These stages include; The first of these stages is to collect data from hospitals as real data and from Kagglewebsite for patients and healthy people, then the stage before removing the noise and converting it from RGB to grayscale, then we improve the image, segmentation and formalities, the other stage is a stage used to extract the important characteristics, and the last stage is the classification of images CT scan using Feed Forward Back Propagation Network (FFBPN) and Support Vector Machine (SVM )and compare the result between them and see if the person is infected or healthy. This study was implemented in MATLAB software. The results showed that the noise cancellation technology using anisotropic filtering gave the best results. As for the optimization technology, only the brightness of the images has been increased. At the stage of segmentation of the area of ​​lung injection using the area transplant method, the best results are detection of COVID-19 from other healthy tissues. The FFBPN gave the best results for detecting and classifying COVID-19 as well as determining whether a person has been infected or not. The results of the proposed methodology in accurate and rapid detection of COVID-19 in the lung. The contribution of this paper is to help medical staff detect COVID-19 without human intervention.

Performance enhancement for visible light communication based ADO-OFDM

The increasing demand for bandwidth through modern applications and multimedia services has led to high-speed wireless communications. Optical wireless communications (OWC) encourages solutions that provide a higher data rate due to the large bandwidth available. In this paper, performance enhancement approaches are studied and simulated for visible light communication (VLC) as a case study. The orthogonal frequency division multiplexing (OFDM) systems are used to investigate Intensity modulation/direct detection (IM/DD) to improve the performance of VLC. The IM/DD in OWC requires positive real OFDM symbols, so there are many approaches to satisfy this requirement. This paper proposes a model of Asymmetrically Clipped DC-Biased Optical (ADO-OFDM) to use in OWC/VLC environment. The proposed system has avoided the use of the noise cancellation technology that is used in traditional ADO-OFDM. The results show that the ADO-OFDM has the best spectral efficiency than DC-biased optical (DCO-OFDM) and Asymmetrically clipped optical (ACO-OFDM). Also, it has better optical efficiency than DCO-OFDM with the equally overall bit error rate (BER) at the same signal-to-noise ratio. Hamming channel coding/decoding with different code lengths is applied in various optical OFDM schemes for BER improvements. Furthermore, we simulate and analyze these optical OFDM systems with many modulation orders.

RETRACTED ARTICLE: Research on implementation of adaptive noise cancellation system based on neural network

In this paper, neural network is applied to adaptive noise cancellation technology, and an improved BP algorithm for adaptive noise cancellation is proposed. Firstly, the principle of adaptive noise cancellation technology is introduced briefly, and then some commonly used adaptive algorithms in noise cancellation technology are summarized. Then the adaptive noise cancellation system based on neural network is simulated in MATLAB from two aspects. When two noise signals are linearly correlated, two different signals are used to simulate the system. The advantages and disadvantages of each algorithm are verified by comparing the simulation results. Two different input signals are used to analyze the ability of removing noise when two noise signals are non-linearly correlated, and the adaptive noise cancellation system based on LMS is compared. Finally, the performance of the system is analyzed from three aspects: denoising ability, convergence speed and mean square error. Finally, the measured data are used in the adaptive noise cancellation system. The simulation results verify its effectiveness and the performance of the adaptive noise cancellation system based on neural network is better.

주파수 해석에 따른 저조도 환경의 적응적 잡음제거

CCD 카메라를 이용해 영상을 취득하는 과정에서 조도가 낮을 경우, 자동이득제어(AGC)를 사용하여 자동적으로 부족한 출력 신호를 증폭하게 된다. 이 과정에서 신호와 함께 잡음도 함께 증폭하게 된다. 따라서 저조도 상황에서 취득한 영상은 잡음이 매우 강하여 기존의 방법으로는 잡음을 효과적으로 제거하기 어렵다. 본 논문에서는 잡음의 정도가 심한 저조도 영상의 잡음제거를 위하여 중심화소와 주변영역을 주파수 영역으로 변환하여, 신호 및 잡음의 주파수 특성에 따라 적응적으로 잡음제거를 수행하는 잡음제거 기술을 제안한다. 이러한 주파수 대역 별 특성의 차이를 비교하여 영상의 특징에 따른 적응적인 잡음제거를 수행하여 저조도 환경 영상의 화질을 개선하였다.

Improved Tactical Headset: The Effect of Noise Cancellation on Sound Localization

Among other dangers, soldiers in combat often risk hearing damage. A new source of damage is an increase in crew compartment noise resulting from the addition of armored protection to Highly Mobile Multi-Wheeled Vehicles (HMMWVs, commonly known as “Humvee”). To protect soldiers, the US Army may replace the current Interim Headset (IH) with an Improved Tactical Headset (ITH), which uses noise cancellation technology. However, decision makers are concerned that the ITH may affect perception. In the current study, twenty-one soldiers were tested for accuracy of sound localization in an 8 times 2 mixed experimental design (Speaker Location x Headset Type). Results indicate soldiers wearing either headset experienced the front/back confusion typically found in the literature; but soldiers wearing the ITH localized sound more accurately when the sounds originated from their rear and right rear. These findings may support the ITH as the preferred intervention.

Autonomous acoustic sensing on mobile ground and aerial platforms

Acoustic sensor systems on the ground and/or in the air can be used effectively for autonomous and remote intelligence surveillance and reconnaissance (ISR) applications. Acoustic sensors can be used as primary sensors and/or secondary sensors to cue other higher-resolution sensors for detection, tracking and classification of continuous and transient battlefield acoustic events such as ground vehicles, airborne aircraft, personnel, indirect fire, and direct fire. Current collaborative research activities at ARL in acoustic sensing from mobile ground platforms such as HMMWVs and small robotic vehicles [P. Martin and S. Young, Proc. of SPIE Defense &amp; Security Symposium, 2004] and from aerial platforms such as UAVs and balloons [Reiff, Pham et al, Proc. of the 24th Army Science Conference, 2004] demonstrate practical performance enhancements over fixed ground-based platforms for a number of ISR applications. For both mobile ground and aerial platforms, self-generated noise (flow noise and platform noise) is problematic but they can be suppressed with specialized windscreens, sensor placement, and noise cancellation technology. Typical acoustic detection and processing results for mobile platforms are compared and contrasted against fixed ground-based platforms.

ノイズ除去用ＣＭＯＳ反転アンプ形フレームメモリーを搭載したＣＭＯＳエリア形オートフォーカスセンサ

Abstract We have developed a CMOS area sensor for an auto-focus camera system, our AF SLR (Auto-Focus Single-Lens-Reflex) camera EOS-3 which achieves 45-point area auto focusing. It is fabricated using a 1.2 μm CMOS process technology. This sensor consists of new CMOS sensor cells, new CMOS memory cells, signal transfer circuits, and peak monitor circuits. This device realizes low noise characteristics by new noise cancellation technology. This sensor exhibits excellent performance, such as a high sensitivity of 26.6 V/lx·s and a wide dynamic range of 73.6 dB. It also has low power consumption, high-speed readout, and on-chip peripheral circuits.