• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 추계학술대회 논문집
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• pp.345-351
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• 2004

This Paper describes a nonlinear adaptive noise filter using neural network for digital controller system. Back-Propagation Learning Algorithm based MLP (Multi Layer Perceptron)is used an adaptive filters. In this paper. it assume that the noise of primary input in the adaptive noise canceller is not the same characteristic as that of the reference input. Experimental reaults show that the neural network base noise canceller outperforms the linear noise canceller. Especially to make noise cancel close to realtime, Primary input is divided by unit and each divided part is processed for very short time than all the processed data are unified to whole data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.16-19
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• 1996

The objective of this paper is to present a new adaptive nonlinear compensation method, which is based upon the Pth-order inverse theory and can be implemented in a systematic way, for weakly nonlinear systems that can be modeled by a Volterra series. In particular, employment of the proposed approach for the linearization of a given nonlinear system leads to the effective elimination of (up to a required order) nonlinearities in the overall system output. To demonstrate the feasibility of the proposed method, simulation results using a satellite communication system model are also provided.

• 대한전기학회논문지:전기물성ㆍ응용부문C
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• 제48권1호
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• pp.45-50
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• 1999

This paper describes a partial discharge (PD) on-line monitoring system used for large turbine generators. The system consists of a broadband current transducer, a computer-aid PD measurement system. By using a programmable fabricate band pass filter and an adaptive digital filter, the system can suppress the noise and extract PD signal from the intense noise surroundings successfully. Two simulated PD sources, which often exist in the large generators, were simulated and detected. At the end of this paper, some field test results, obtained from a 200MW generating set, were presented and discussed.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2013년도 추계학술대회
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• pp.268-270
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• 2013

Wibro 기술의 개발 및 보급으로 인하여, 디지털 기술이 여러 분야에서 활용되고 있다. 디지털 영상은 전송 및 저장하는 과정에서 다양한 잡음에 의해 훼손되며, 영상복원은 영상에 첨가되는 잡음을 제거하여 잡음이 영상에 미치는 영향을 줄이는 것이다. 영상복원을 위해, 여러 가지 방법들이 제안되었으나 기존의 방법들은 잡음제거 특성이 미흡하다. 따라서 본 논문에서는 효과적으로 잡음을 제거하기 위해 잡음판단을 거쳐, 잡음일 경우, 마스크 크기를 확대시키는 적응 메디안 필터 알고리즘을 제안하였다. 그리고 시뮬레이션을 통해 기존의 방법들과 비교하여 제안한 알고리즘의 우수성을 입증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권7호
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• pp.2356-2376
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• 2021

In this paper, we proposed a novel modulation recognition method based on quantum elephant herding algorithm (QEHA) evolving neural network under impulse noise environment. We use the adaptive weight myriad filter to preprocess the received digital modulation signals which passing through the impulsive noise channel, and then the instantaneous characteristics and high order cumulant features of digital modulation signals are extracted as classification feature set, finally, the BP neural network (BPNN) model as a classifier for automatic digital modulation recognition. Besides, based on the elephant herding optimization (EHO) algorithm and quantum computing mechanism, we design a quantum elephant herding algorithm (QEHA) to optimize the initial thresholds and weights of the BPNN, which solves the problem that traditional BPNN is easy into local minimum values and poor robustness. The experimental results prove that the adaptive weight myriad filter we used can remove the impulsive noise effectively, and the proposed QEHA-BPNN classifier has better recognition performance than other conventional pattern recognition classifiers. Compared with other global optimization algorithms, the QEHA designed in this paper has a faster convergence speed and higher convergence accuracy. Furthermore, the effect of symbol shape has been considered, which can satisfy the need for engineering.

• ETRI Journal
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• 제38권1호
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• pp.164-173
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• 2016

Demosaicing, or color filter array (CFA) interpolation, estimates missing color channels of raw mosaiced images from a CFA to reproduce full-color images. It is an essential process for single-sensor digital cameras with CFAs. In this paper, a new demosaicing method for digital cameras with Bayer-like W-RGB CFAs is proposed. To preserve the edge structure when reproducing full-color images, we propose an edge direction-adaptive method using color difference estimation between different channels, which can be applied to practical digital camera use. To evaluate the performance of the proposed method in terms of CPSNR, FSIM, and S-CIELAB color distance measures, we perform simulations on sets of mosaiced images captured by an actual prototype digital camera with a Bayer-like W-RGB CFA. The simulation results show that the proposed method demosaics better than a conventional one by approximately +22.4% CPSNR, +0.9% FSIM, and +36.7% S-CIELAB distance.

• 한국정보전자통신기술학회논문지
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• 제11권5호
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• pp.538-542
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• 2018

디지털보청기 벤트에서 발생되는 반향은 사용자의 불편을 초래한다. 벤트에서 귀환되는 반향을 제거하기 위해서는 귀환경로인 벤트의 임펄스응답의 정확한 추정이 요구된다. 벤트의 임펄스응답은 시간에 따라 변하는 특성과 함께 성긴 특성을 가진다. 이러한 특성의 벤트 임펄스응답 추정에 유용한 적응 알고리즘으로는 IPNLMS가 유용한 것으로 알려져 있다. 본 논문에서는 벤트의 성긴 임펄스응답을 추정하여 벤트에 의한 반향의 제거를 위해 IPNLMS를 부밴드 보청기 구조에 적용하는 부밴드 성긴 적응필터를 제안한다. 제안 기법에서 신호의 부밴드 분해는 각 대역 신호의 사전백색화가 가능하므로 적응필터의 수렴속도의 개선이 가능하다. 그리고 적응필터의 다위상 분해는 각 다위상 성분 필터에서 성긴도를 증가시키며, 추가 계산 없이 반향제거 성능개선이 가능하다. 제안 적응필터의 계수갱신 식 유도를 위해 가중 NLMS에 근거한 비용함수를 정의하고 이를 이용 각부밴드에서 적응필터의 계수 갱신 식을 유도한다. 제안한 적응필터의 성능검증을 위해 백색신호를 입력으로 하여 수렴속도와 정상상태오차를, 실제 음성신호를 입력으로 하여 반향제거 결과를 기존 알고리즘과 비교 평가한다.

• 한국통신학회논문지
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• 제21권9호
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• pp.2456-2469
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• 1996

A digital satellite communication channel has a nonlinearity with memory due to saturation characeristis of the high poer amplifier in the satellite and transmitter/receiver linear filter used in the overall system. In this paper, we propose a complex radial basis function network(CRBFN) based adaptive equalizer for compensation of nonlinearities in digital satellite communication channels. The proposed CRBFN untilizes a complex-valued hybrid learning algorithm of k-means clustering and LMS(least mean sequare) algorithm that is an extension of Moody Darken's algorithm for real-valued data. We evaluate performance of CRBFN in terms of symbol error rates and mean squared errors nder various noise conditions for 4-PSK(phase shift keying) digital modulation schemes and compare with those of comples pth order inverse adaptive Volterra filter. The computer simulation results show that the proposed CRBFN ehibits good equalization, low computational complexity and fast learning capabilities.

• 대한전기학회논문지:시스템및제어부문D
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• 제51권10호
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• pp.468-476
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• 2002

Digital images are easily corrupted by noise during the data transmission, data capture and data processing. A technical method of noise analyzing and adaptive filtering for reducing of quantum noise in medical radio-fluoroscopy images is presented. By adjusting the characteristics of the filter according to local statistics around each pixel of the image as moving windowing, it is possible to suppress noise sufficiently while preserve edge and other significant information required in diagnosis. We proposed adaptive weighed median(AWM) filters based on local statistics. We showed two ways of realizing the AWM filters. One is a simple type of AWM filter, which is constructed by Homogeneous factor(HF). Homogeneous factor(HF) from the noise models that enables the filter to recognize the local structures of the image is introduced, and an algorithm for determining the HF fitted to the diagnostic systems with various inner statistical properties is proposed. We show by the experimented that the performances of proposed method is superior to these of other filters and models in preserving small details and suppressing the noise at homogeneous region. The proposed algorithms were implemented by Visual C++ language on a IBM-PC Pentium 550 for testing purposes and the effects and results of the filter in the various levels of noise and images were proposed by comparing the values of NMSE(normalized mean square error) with the value of the other existing filtering methods.

• 한국정보통신학회논문지
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• 제17권5호
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• pp.1227-1232
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• 2013

현재, 디지털 시대의 급속 발전과 함께 디지털 장치에 대한 수요가 급격히 성장되면서 영상의 화질에 대한 기대가 증가되고 있다. 그러나 영상은 여러 가지 원인에 의해 훼손되며, 그 주요원인은 잡음에 의한 것이다. 따라서 잡음제거에 대한 필요성이 대두되고 있으며, 잡음제거를 위한 활발한 연구가 진행되고 있다. 영상은 AWGN(additive white Gaussian noise)에 의해 많이 훼손되며, 평균 필터(mean filter) 등 기존의 방법들은 잡음제거 특성이 다소 미흡하다. 본 논문에서는 AWGN을 효과적으로 제거하기 위하여, 공간 가중치와 변형된 적응 가중치를 결합한 알고리즘을 제안하였다. 시뮬레이션 결과, 제안한 방법은 우수한 잡음제거 특성을 나타내었다.