• 한국음향학회지
• /
• 제22권5호
• /
• pp.351-359
• /
• 2003

본 논문에서는 독립성분분석을 이용한 음향 반향제거 방법을 제안하였다. 음향반향제거기의 마이크로폰에 반향 이외의 잡음이 부가될 경우 반향제거기의 성능은 저하된다. 이러한 문제를 해결하기 위해 본 연구에서는 두 개의 마이크로폰을 이용하여 반향과 선형으로 섞인 잡음을 받은 후 독립성분 분석 기법을 통해 반향과 잡음을 분리하였다. 그리고 분리된 반향 신호를 반향제거기에 사용되는 적응 알고리듬의 기준 신호로 이용함으로서 반향제거기의 성능을 향상시켰다. 컴퓨터 모의실험을 통해 제안한 방법의 타당성을 확인하였다.

• 전기학회논문지
• /
• 제56권7호
• /
• pp.1191-1198
• /
• 2007

In this paper, the fault detection and noise cancellation algorithm based on wavelet transform was developed to locate the fault more accurately. Specially, noise cancellation algorithm was based on the correlation of wavelet coefficients at multi-scales. Fault detection, classification and location algorithm were tested by EMTP simulation on real power cable system. From these results, the faults can be detected and located even in very difficult situations, such as at different inception angle and fault resistance.

• 전기학회논문지
• /
• 제58권4호
• /
• pp.857-866
• /
• 2009

In this paper, a noise cancellation-method using microphone array for digital hearing aids is proposed. The microphone array is located around the ear of a dummy. Speech sound is generated from the forward speaker positioned in the front of the dummy and noise sound is generated from the backward speaker. The speech and noise are mixed in the air space and entered into the microphones. VAD(voice activity detector) and ANC(adaptive noise cancellation) methods were used to eliminate noise in the sound of the microphones. 10 two-syllable words and 4 sentences were used for speech signals. Babble and car interior noise were used for noise signals. The performance of the proposed algorithm was evaluated by SNR(signal-to-noise ratio) and PESQ-MOS(perceptual evaluation of speech quality-mean opinion score). In babble noise condition, SNR was improved as much as $7.963{\pm}1.3620dB\;and\;3.968{\pm}0.6659dB$ for words and sentences respectively. In the case of car interior noise, SNR was improved as $10.512{\pm}2.0665dB\;and\;6.000{\pm}1.7642dB$ for words and sentences respectively. PESQ-MOS of the babble noise was improved as much as $0.1722{\pm}0.0861$ score for words and $0.083{\pm}0.0417$ score for sentences. And PESQ-MOS of the car interior noise was improved as $0.2661{\pm}0.0335$ score and $0.040{\pm}0.0201$ score for words and sentences respectively. It is verified that the proposed algorithm has a good performance in noise cancellation of microphone array for digital hearing aids.

• 제어로봇시스템학회논문지
• /
• 제7권11호
• /
• pp.891-895
• /
• 2001

An alternative inverse feedback structure for adaptive active control of periodic noise is introduced for systems with nonminimum phase cancellation path. To obtain the inverse model of the nonminimum phase cancellation path, the cancellation path model can be factorized into a minimum phase term and a maximum phase term. The maximum phase term containing unstable zeros makes the inverse model unstable. To avoid the instability, we alter the inverse model of the maximum phase system into an anti-causal FIR one. An LMS predictor estimates the future samples of the noise, which are necessary for causality of both anti-causal FIR approximation for the stable inverse of the maximum phase system and time-delay existing in the cancellation path. The proposed method has a faster convergence behavior and a better transient response than the conventional filtered-x LMS algorithms with the same internal model control structure since a filtered reference signal is not required. We compare the proposed methods with the conventional methods through simulation studies.

• 한국소음진동공학회논문집
• /
• 제13권7호
• /
• pp.499-507
• /
• 2003

This paper presents a method for active noise control (ANC) in a duct by using a ring-tyPe smart foam. The ring-type smart foam consists of an elastic porous material of lining shape and a PVDF film embedded In the material. The PVDF element acts as a secondary sound source to reduce the noise. Active noise control using a ring-type smart foam is only effective locally because of the way to excite radially. To enlarge the quiet zone, the duct Is lined with additional acoustic foam between the smart foam and the error microphone. When cancellation path ks optimized by the LMS/RLS algorithm, the computation power is reduced while control performance Is maintained. The filtered-x LMS algorithm is used to minimize the error signal.

• 전기학회논문지
• /
• 제57권2호
• /
• pp.184-190
• /
• 2008

The fault location algorithm based on stationary wavelet transform was developed to locate the fault point more accurately. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. In previous paper, noise cancellation technique based on the correlation of wavelet coefficients at multi-scales was introduced, and the efficiency was also proved in full. In this paper, fault section discrimination and fault location algorithm using noise cancellation technique were tested by ATP simulation on real power cable systems. From these results, the fault can be located even in very difficult and complicated situations such as different inception angle and fault resistance.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
• /
• pp.2244-2247
• /
• 2003

In this paper, we present a method which can minimize distortion from desired signal in thoracic sound signal processing. We firstly chose the proper wavelet mother function to reduce noise components. Secondly, we chose a clean thoracic sound, then added Gaussian noise and 3 step(10, 15, 20db) uniform noise to it. Finally, the various wavelet functions are applied for noise cancellation. To evaluate the efficiency of this study, we computed SNR and RSE value. Then we found the optimal mother wavelet function for thoracic sound.

• 한국인터넷방송통신학회논문지
• /
• 제19권2호
• /
• pp.41-45
• /
• 2019

본 논문은 스마트 그리드를 위한 전력선 통신 시스템에서 데이터 신뢰성을 향상시키는 딥러닝 기반의 종단 간 방식의 간섭 제거 알고리즘에 대해 연구하였다. 본 논문에서 제안한 기법은 딥러닝 기술을 적용하여 채널에서 발생하는 잡음을 예측하여 제거하는 기술로서 수신단에서 딥러닝에 의해 학습된 잡음들을 활용하여 효과적으로 잡음을 제거함으로써 신호의 품질을 향상시킬 수 있다. 딥러닝 기술의 잡음 예측 정확도를 향상시키기 위해 기존의 잡음 형태를 데이터베이스화하여 활용하였다. 채널 모델로서 Middleton Class A 간섭 모델을 사용하였고, 비트 오류율을 평가하여 성능을 검증하였다. 모의실험을 통해 간섭 제거 기법이 적용된 시스템 모델과 이론적인 모델의 비트오류율을 비교하여 제안하는 시스템이 잡음을 효과적으로 제거하여 신호의 품질 성능을 향상시킬 수 있음을 확인하였다. 제안한 시스템 모델은 전력선 통신뿐만 아니라 일반적인 통신 시스템에서도 신호의 품질을 향상시킬 수 있도록 다양하게 적용이 가능하다.

• 대한음성학회지:말소리
• /
• 제52호
• /
• pp.121-132
• /
• 2004

This paper is aiming at real-time implementation of adaptive noise cancellation system using DSP processor. ACHARF algorithm, which guarantees stability and fast convergence by adaptive compensator, is used on this DSP system. For the experiments, TLV320AIC23 stereo CODEC of TI Inc. is used with TMS320C6413 DSP processor. Signals of primary input and reference input are obtained by two microphones. The primary input is the voice plus noise signal and the reference input is white noise or real noise. The experimental results show that ANC system using DSP processor with ACHARF is verified to be an effective speech enhancement method for various speech processing units.

• 소음진동
• /
• 제10권6호
• /
• pp.941-948
• /
• 2000

Active noise control is an approach to reduce the noise by utilizing a secondary noise source that destructively interferes with the unwanted noise. In general, active noise control systems rely on multiple sensors to measure the unwanted noise field and the effect of the cancellation. This paper develops an approach that utilizes a single sensor. The noise field is modeled as a stochastic process, and an adaptive algorithm is used to adaptively estimate the parameters of the process. Based on these parameter estimates, a canceling signal is generated. Oppenheim assumed that transfer function characteristics from the canceling source to the error sensor is only a propagation delay. This paper proposes a modified Oppenheim algorithm by considering transfer characteristics of speaker-path-sensor This transfer characteristics is adaptively cancelled by the proposed adaptive modeling technique. Feasibility of the proposed method is proved by computer simulations with artificially generated random noises and sine wave noise. The details of the proposed architecture. and theoretical simulation of the noise cancellation system for three dimension enclosure are presented in the Paper.