• Journal of information and communication convergence engineering
• /
• 제20권2호
• /
• pp.73-78
• /
• 2022

Based on experimental measurements conducted on many different practical wireless communication systems, ambient noise has been shown to be decidedly non-Gaussian owing to impulsive phenomena. However, most multiuser detection techniques proposed thus far have considered Gaussian noise only. They may therefore suffer from a considerable performance loss in the presence of impulsive ambient noise. In this paper, we consider a large-scale multiuser multiple-input multiple-output system in the presence of non-Gaussian noise and propose a genetic algorithm (GA) based detector for large-dimensional multiuser signal detection. The proposed algorithm is more robust than linear multi-user detectors for non-Gaussian noise because it uses a multi-directional search to manipulate and maintain a population of potential solutions. Meanwhile, the proposed GA-based algorithm has a comparable complexity because it does not require any complicated computations (e.g., a matrix inverse or derivation). The simulation results show that the GA offers a performance gain over the linear minimum mean square error algorithm for both non-Gaussian and Gaussian noise.

• ETRI Journal
• /
• 제35권4호
• /
• pp.644-654
• /
• 2013

In this paper, a signal detection scheme for cognitive radio (CR) based on the Bussgang theorem is proposed. The proposed scheme calculates the statistical difference between Gaussian noise and the primary user signal by applying the Bussgang theorem to the received signal. Therefore, the proposed scheme overcomes the noise uncertainty and gives scalable complexity according to the zero-memory nonlinear function for a mobile device. We also present the theoretical analysis on the detection threshold and the detection performance in the additive white Gaussian noise channel. The proposed detection scheme is evaluated by computer simulations based on the IEEE 802.22 standard for the wireless regional area network. Our results show that the proposed scheme is robust to the noise uncertainty and works well in a very low signal-to-noise ratio.

• 대한전자공학회논문지
• /
• 제13권5호
• /
• pp.24-29
• /
• 1976

Phase locked AM신호 검파방식에서는 위상고정회로를 사용하여 입력신호로부터 반송신호를 분리 재생시킨다. 입력잡음은 백색 Gaussian잡음이고, 전려제어발진기의 자유발진주파수와 입력반송신호주파수가 같다는 가정하에 위상고정회로의 동작특성을 해석하고, 본 검파방식의 신호대 잡음비를 정량적으로 고찰하였다. Phase locked AM신호 검파방식은 종래의 검파방식에 비해서 잡음의 영향을 적게 받게됨을 본 해석에서 알 수 있다. In the phase locked AM signal detection, phase locked loop is used to extract a synchronous carrier from an input AM signal. Under the assumption that input noise is white Gaussian and free-running frequency of voltage controlled oscillator is the same that of an input carrier, operational behaviours of phase locked loop is analyzed and signal to noise ratio of the detection is derived quentitatively. The results show that the phase locked AM signal detection method offers a higher degree of noise mmunity than conventional AM signal detections.

• 한국정밀공학회지
• /
• 제9권2호
• /
• pp.128-137
• /
• 1992

An automatic noise detection system is developed to sense abnormal noises in operating a microwave electronic range. A noise detection method is presented which accounts for the effects of backgound and dynamic noises of the range. A recursive formula used as a noise estimator is a special case of the discrete-time Kalman filter in stochastic processes. Noise levels were measured using a noise acquisition processor in a closed room free of background noise, and detected signals were processes using a microcomputer. The results obtaines showed that the fault detection system should be fast in response to the data acquired and should be high in accuracy and reliability.

• Journal of Information Processing Systems
• /
• 제9권1호
• /
• pp.89-102
• /
• 2013

The paper presents a fuzzy based impulse noise filter for both gray scale and color images. The proposed approach is based on the technique of boundary discriminative noise detection. The algorithm is a multi-step process comprising detection, filtering and color correction stages. The detection procedure classifies the pixels as corrupted and uncorrupted by computing decision boundaries, which are fuzzified to improve the outputs obtained. In the case of color images, a correction term is added by examining the interactions between the color components for further improvement. Quantitative and qualitative analysis, performed on standard gray scale and color image, shows improved performance of the proposed technique over existing state-of-the-art algorithms in terms of Peak Signal to Noise Ratio (PSNR) and color difference metrics. The analysis proves the applicability of the proposed algorithm to random valued impulse noise.

• 대한음성학회지:말소리
• /
• 제48호
• /
• pp.155-173
• /
• 2003

This paper proposes a noise reduction-based speech detection method under telephone channel environments. We adopt the AURORA front-end noise reduction algorithm based on the two-stage mel-warped Wiener filter approach as a preprocessor for the frequency domain speech detector. The speech detector utilizes mel filter-bank based useful band energies as its feature parameters. The preprocessor firstly removes the adverse noise components on the incoming noisy speech signals and the speech detector at the next stage detects proper speech regions for the noise-reduced speech signals. Experimental results show that the proposed noise reduction-based speech detection method is very effective in improving not only the performance of the speech detector but also that of the subsequent speech recognizer.

• 대한전기학회논문지:시스템및제어부문D
• /
• 제54권3호
• /
• pp.166-173
• /
• 2005

Preserving image features, edges and details in the process of impulsive noise filtering is an important problem. To avoid image blurring, only corrupted pixels must be filtered. In this paper, we propose an effective impulse noise detection method using Self-Organizing Neural Network(SONN) which applies median filter selectively for removing random-valued impulse noises while preserving image features, edges and details. Using a $3\times3$ window, we obtain useful local features with which impulse noise patterns are classified. SONN is trained with sample image patterns and each pixel pattern is classified by its local information in the image. The results of the experiments with various images which are the noise range of $5-15\%$ show that our method performs better than other methods which use multiple threshold values for impulse noise detection.

• 한국전자파학회논문지
• /
• 제11권2호
• /
• pp.228-233
• /
• 2000

본 논문에서는 무선광연결에서 끈사적 평균잡음검출을 이용한 차동검출방식에 대하여 소개한다 이 방식은 기존의 잠음광의 영향을 소거하는 차동검출기의 기능을 보완한다. 근사적 평균잡음전압을 이용하여 차동검출하면. 물체나 사람의 이동에 의하여 나타날 수 있는 잡음광 결합비의 순간적 변화에 의한 출력전압의 변동을 줄일 수 있다 이 것은 장음광의 공간적 분포가 수시로 변동하는 환경에서 무선광연결을 구성하는 경우 잡음광을 소거하는 데에 매우 효과적이다

• 전자공학회논문지
• /
• 제52권4호
• /
• pp.207-212
• /
• 2015

움직임 영상에서 에지 검출을 이용하여 잡음을 예측하는 방법을 제안한다. 에지 검출은 잡음 예측에 영향을 주는 구조와 세밀함을 제거하는 역할을 한다. 에지를 검출하기 위하여 잡음에 강한 소벨과 형상학 닫힘 연산자를 사용한다. 제안하는 잡음 예측 방법은 다양한 종류의 동영상에 효율적으로 적용될 수 있으며 기존 잡음 예측 방법들 보다 향상된 결과를 가진다. 또한, 제안하는 알고리즘은 영상과 비디오 응용에서 효율적으로 적용할 수 있다.

• 음성과학
• /
• 제5권1호
• /
• pp.81-88
• /
• 1999

This paper provides a method for speech detection. After first order FIR filtering on the speech signals, we applied the conventional method of endpoint detection which utilizes the energy as the criterion in separating signals from background noise. By FIR filtering, only the Fourier components with large values of [amplitude x frequency] become significant in energy profile. By applying this procedure to the 445-words database constructed from ETRI, we confirmed that the low-amplitude noise and/or the low-frequency noise are separated clearly from the speech signals, thereby enhancing the feasibility of ideal endpoint detections.