• 한국콘텐츠학회논문지
• /
• 제8권4호
• /
• pp.79-85
• /
• 2008

현재 많은 광대역 전송 시스템의 변복조 방식으로 직교 주파수 분할 다중화(orthogonal frequency division multiplexing: OFDM) 방식이 널리 사용되고 있다. OFDM 방식은 기저파형으로 서로 직교하는 정현파를 사용하는 직교 파형 변조의 하나이다. 이 논문에서는 기저파형으로 정현파 대신 웨이블릿 패킷을 사용하는 웨이블릿 패킷 변조에 대해 살펴보고자 한다. 웨이블릿 패킷은 시간-주파수 2차원 평면에서 서로 다른 모양을 가질 수 있기 때문에 채널환경에 따라 그에 적합한 파형을 쉽게 설계할 수 있다. 이 논문에서는 다중반송파 변조방식의 다른 형태로서 웨이블릿 패킷 변조의 특징에 대해 살펴보고, 협대역 간섭 환경에서 대역폭을 유연하게 조절함으로써 간섭의 영향을 감소시킬 수 있음을 보이고자 한다.

• Progress in Superconductivity
• /
• 제4권1호
• /
• pp.53-58
• /
• 2002

Noise from electronic instrumentation is invariably present in biomedical signals, although the art of instrumentation design is such that this noise source may be negligible. And sometimes signals of interest are contaminated or degraded by signals of similar type from another source. Biomedical signals are omni-presently contaminated by these background noises that span nearly all frequency bandwidths. In the magneto-cardiogram (MCG), several digital filters have been designed for the elimination of the power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. In addition to the introduced FIR filter, notch, adaptive filter using the least mean square (LMS) algorithm, and recurrent neural network (RNN) filter, a new filtering method for effective noise canceling in MCG signals is proposed in this paper, which is realized by the wavelet packets. The experimental results show that the proposed filter using wavelet packet performs efficiently with respect to noise rejection. To verify this, two characteristics were analyzed and compared with LMS adaptive filter, SNR of filtered signal and attractor pattern using the nonlinear dynamics.

• 한국통신학회논문지
• /
• 제31권6C호
• /
• pp.589-602
• /
• 2006

잡음은 음성과 관련된 시스템의 성능을 제한하는 주된 원인이기 때문에 음성향상과 관련된 연구는 꾸준히 계속되어왔다. 전통적인 음성향상 방법은 무성음과 잡음을 구분하지 알기 때문에 잡음제거 과정에서 무성음이 함께 제거되는 단점이 있으며, 웨이블릿 기반의 전통적인 잡음제거 방법은 각 대역마다 동일한 문턱값을 사용하기 때문에 시변 환경에서 성능이 떨어지는 단점이 있다. 이 단점들을 개선하기위해 다중대역 파워 차감법과 Perceptual 웨이블릿 패킷 분해를 이용한 웨이블릿 기반의 개선된 음성향상 방법을 제안한다. 전처리 과정으로 다중대역 파워 차감법을 사용하여 광대역 잡음을 제거하고 뮤지컬 잡음의 발생을 줄이며, psycho-acoustic 모델 기반 Perceptual 웨이블릿 패킷으로 신호를 분해한 후 각 웨이블릿 노드의 엔트로피 비율과 음성검출을 이용하여 무성음/유성음/잡음을 구분한다. 구분된 신호에 따라 각 웨이블릿 노드마다의 문턱값을 기준으로 웨이블릿 Shrinkage를 적용하여 잡음을 제거하고 무성음이나 파워가 작은 유성음이 제거되는 오류를 최소화한다. 또한 잡음 파워 추정 과정에 적응적으로 망각 계수를 선택하여 잡음 파워 추정 오류를 최소화한다.

• Progress in Superconductivity
• /
• 제5권1호
• /
• pp.26-30
• /
• 2003

Magneto-cardiogram(MCG) signals may be highly distorted by the environmental noise, such as power-line interference, broadband white noise, surrounding magnetic noise, and baseline wondering. Several kinds of digital filters and noise cancellation methods have been designed and realized by many researchers, but these methods gave some problems that the original signal may be distorted by digital filter due to the wideband characteristics of background noise. To eliminate noise effectively without distortion of MCG signals, we performed multi-level frequency decomposition using wavelet packets and local adaptive noise cancellation in each local frequency range. In addition to the proposed wavelet filter to eliminate these various non-stationary noise elements, the local adaptive filter using the least mean square(LMS) algorithm and the soft threshold do-noising method are introduced in this paper. The signal to noise ratio(SNR) and the reconstruction square error(RSE) are calculated to evaluate the performance of the proposed method and compared with the results of the conventional wavelet filter and adaptive filter. The experimental results show that the proposed local adaptive filtering method is better than the conventional methods.

• International Journal of Control, Automation, and Systems
• /
• 제6권4호
• /
• pp.526-533
• /
• 2008

We propose a wavelet neural network (WNN) control method for active queue management (AQM) in an end-to-end TCP network, which is trained by adaptive learning rates (ALRs). In the TCP network, AQM is important to regulate the queue length by passing or dropping the packets at the intermediate routers. RED, PI, and PID algorithms have been used for AQM. But these algorithms show weaknesses in the detection and control of congestion under dynamically changing network situations. In our method, the WNN controller using ALRs is designed to overcome these problems. It adaptively controls the dropping probability of the packets and is trained by gradient-descent algorithm. We apply Lyapunov theorem to verify the stability of the WNN controller using ALRs. Simulations are carried out to demonstrate the effectiveness of the proposed method.

• 한국초전도학회:학술대회논문집
• /
• 한국초전도학회 2003년도 High Temperature Superconductivity Vol.XIII
• /
• pp.43-43
• /
• 2003

• 한국섬유공학회:학술대회논문집
• /
• 한국섬유공학회 1999년도 봄 학술발표회 논문집
• /
• pp.115-119
• /
• 1999

• 한국섬유공학회:학술대회논문집
• /
• 한국섬유공학회 2001년도 학술발표회 논문집(Proceedings of the Korean Textile Conference)
• /
• pp.161-163
• /
• 2001

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 하계학술대회 논문집 D
• /
• pp.3028-3030
• /
• 2000

In general. a speech coding is dedicated to the compression performance or the speech quality. But. the speech coding in this paper is focused on the performance of flexible transmission to the, network speed. For this. the subbanding coding is needed. which is used the wavelet packet concept in the signal analysis. The extraction of each frequency-band is difficult to general signal analysis methods, after coding each band, the reconstruction of these is also a difficult problem. But. with the wavelet packet concept(perfect reconstruction) and its fast computation algorithm. the extraction of each band and the reconstruction are more natural. Also, this paper describes a direct solution of the voice transmission on network and implement this algorithm at the TCP/IP network environment of PC.

• Structural Engineering and Mechanics
• /
• 제37권6호
• /
• pp.575-592
• /
• 2011

For seismic resistant design of critical structures, a dynamic analysis, either response spectrum or time history is frequently required. Owing to the lack of recorded data and the randomness of earthquake ground motion that may be experienced by structure in the future, usually it is difficult to obtain recorded data which fit the requirements (site type, epicenteral distance, etc.) well. Therefore, the artificial seismic records are widely used in seismic designs, verification of seismic capacity and seismic assessment of structures. The purpose of this paper is to develop a numerical method using Artificial Neural Network (ANN) and wavelet packet transform in best basis method which is presented for the decomposition of artificial earthquake records consistent with any arbitrarily specified target response spectra requirements. The ground motion has been modeled as a non-stationary process using wavelet packet. This study shows that the procedure using ANN-based models and wavelet packets in best-basis method are applicable to generate artificial earthquakes compatible with any response spectra. Several numerical examples are given to verify the developed model.