• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.11a
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• pp.238-242
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• 1998

본 논문에서는 간섭 제거기가 다중 톤 DS/CDMA 시스템의 성능에 미치는 영향을 분석하였다. 최근 여러 가지 방법의 간섭 제거기가 제안되고 있으나, 여기서는 Yoon[4] 등이 제안한 간섭 제거기를 사용하였다. 또한 세 가지 종류의 간섭을 고려하였는데 다중 경로 간섭, 채널 간 간섭, 다중 접속 간섭이 그것이다. 이들 간섭 신호들과 가우시안 잡음의 분산을 구하여 신호 대 잡음비를 계산하였으며, 다중 경로 채널에서의 RAKE 수신기와 3단계의 간섭 제거기를 고려하였다. 성능 분석 결과, 간섭 제거기는 다중 톤 CDMA 시스템에서 매우 효과적이며, 최대비 결합 다이버시티와 심볼 당 칩 수를 사용함에 따라 성능이 크게 향상되어 이들 파라메터가 중요한 설계 요소가 될 수 있음을 알 수 있었다.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2002-2004
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• 2003

본 논문에서는 시스템의 모델 불확실성과 백색 가우시안이 아닌 $L_2$ 잡음이 존재하는 경우에 시스템 상태변수의 효과적인 추정을 위한 강인 필터를 제안한다. 제안된 필터는 적분이차제약조건(integral quadratic constraint)을 갖는 일반적인 비선형 불확실 시스템을 위해 선형근사화를 통하여 구성된다. 또한 제안된 필터의 중요한 특성인 변형된 $H{\infty}$ 성능 지수를 유도하고, 해석적 방법을 통해 제안된 필터의 잡음과 시스템 파라미터 불확실성에 대한 강인성을 분석하며, 시뮬레이션 결과를 통하여 제안된 필터가 추정치의 정확도를 효과적으로 향상시키는 것을 보인다.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.4
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• pp.464-471
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• 1999

DS/CDMA 시스템은 이동통신 시스템에서 다중경로, 고의적인 반방해 전파 및 동일대역폭을 공유하기 위한 다중 사용자에 의해 발생되는 협대역 간섭과 부가적인 백색가우시안 잡음을 제거한다. 본 논문에서는 다계층 퍼셉트론을 기반으로 한 역전파 신경망을 이용한 정합필터 채널 모델이 DS/CDMA 이동 통신 시스템에서 직접 순차 확산 스펙트럼의 협대역 간섭을 고려하면서 신호 대 잡음비와 전송 전력비에 따른 컴퓨터시뮬레이션 결과는 역전파 신경망을 이용한 정합 필터의 비트 에러율이 직접 순차 확산 스펙트럼의 RAKE 수신기의 비트 에러 율보다 적음을 입증하였다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.1-10
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• 2007

Most of natural images have a special property, what is called self-similarity, which is the basis of fractal image coding. Even though an image has local stationarity in several homogeneous regions, it is generally non-stationarysignal, especially in edge region. This is the main reason that poor results are induced in linear techniques. In order to overcome the difficulty we propose a non-linear technique using self-similarity in the image. In our work, an image is classified into stationary and non-stationary region with respect to sample variance. In case of stationary region, do-noising is performed as simply averaging of its neighborhoods. However, if the region is non-stationary region, stationalization is conducted as make a set of center pixels by similarity matching with respect to bMSE(block Mean Square Error). And then do-nosing is performed by Gaussian weighted averaging of center pixels of similar blocks, because the set of center pixels of similar blocks can be regarded as nearly stationary. The true image value is estimated by weighted average of the elements of the set. The experimental results show that our method has better performance and smaller variance than other methods as estimator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.9
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• pp.972-981
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• 1992

In this paper, the performance of linear and hard-limiting correlation receivers for DS/SSMA BPSK power line communication system is analyzed. Strong impulsive noise of power line is modeled with Chan's noise model, and the performance of both receivers is analyzed in terms of parameters such as ratio of power spectrum density of impulsive noise to that background noise, ratio in impulsive noise width th that of data bit, and interarrival time of impulsive noise. And also multiple access capacity is evaluated with Gaussian approximation of multiple access interference. The results of this analysis reveal that the performance of linear correlation receiver is superior to that of hard-limiting correlation receiver when $N_1/N_b$ is small and is close to 1. But the BER and the multiple access capacity of hard-limiting correlation receiver becomes better in comparison with linear correlation receiver as $N_1/N_b$ increases.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.772-778
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• 2012

In this paper, the states and the parameters in the dynamic system are simultaneously estimated by applying the UKF(Unscented Kalman Filter), which is widely used for estimating the state of non-linear systems. Estimating the parameter is very important in various fields, such as system control, modeling, analysis of performance, and prediction. Most of the dynamic systems which are dealt with in engineering have non-linearity as well as some noise. Therefore, the parameter estimation is difficult. This paper estimates the states and the parameters applying to the UKF, which is a non-linear filter and has strong noise. The augmented equation is used by including the addition of the parameter factors to the original state equation of the system. Moreover, it is simulated by applying to a 2-DOF(Degree of Freedom) dynamic system composed of the pendulum and the slide. The measurement noise of the dynamic equation is assumed to be a Gaussian distribution. As the simulation results show, the proposed parameter estimation performs better than the LSM(Least Square Method). Furthermore, the estimation errors and convergence time are within three percent and 0.1 second, respectively. Consequentially, the UKF is able to estimate the system states and the parameters for the system, despite having measurement data with noise.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.3
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• pp.23-30
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• 2011

In the wireless sensor network(WSN), the detection of precise location of sensor nodes is essential for efficiently utilizing the sensing data acquired from sensor nodes. Among various location methods, the received signal strength (RSS) based localization scheme is mostly preferable in many applications since it can be easily implemented without any additional hardware cost. Since the RSS localization method is mainly effected by radio channel between two nodes, outlier data can be included in the received signal strength measurement specially when some obstacles move around the link between nodes. The outlier data can have bad effect on estimating the distance between two nodes such that it can cause location errors. In this paper, we propose a RSS-based localization method using Robust Statistic and Gaussian filter algorithm for enhancing the accuracy of RSS-based localization. In the proposed algorithm, the outlier data can be eliminated from samples by using the Robust Statistics as well as the Gaussian filter such that the accuracy of localization can be achieved. Through simulation, it is shown that the proposed algorithm can increase the accuracy of localization and is more robust to non gaussian noise channels.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.66-75
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• 2002

For the theoretical performance analysis of Viterbi Decoder for wireless LAN with data rate 12Mbps, code rate 1/2 and constraint length 7 defined in IEEE 802.11a, the transfer function is derived using Cramer's rule and the first-event error probability and bit error probability is derived under the AWGN. In the design process, input symbol is quantized into 16 steps for 4 bit soft decision and register exchange method instead of memory method is proposed for trace back, which enables the majority at the final decision stage. In the implementation, the Viterbi decoder based on parallel architecture with pipelined scheme for processing 12Mbps high speed data rate and AWGN generator are implemented using FPGA chips. And then its performance is verified in real time.

• The Journal of the Acoustical Society of Korea
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• v.13 no.3
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• pp.16-24
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• 1994

A single channel adaptive noise canceling (ANC) technique is presented for removing effects of additive noise on the speech signal. The conventional method obtains a reference signal using the pitch estimated on a frame basis from the input speech. The proposed method, however, gets the reference signal using the delay estimated recursively on a sample by sample basis. To estimate the delay, we derive recursion formula of autocorrelation function and average magnitude difference function. The performance of the proposed method is evaluated for the speech signals distorted by the additive white Gaussian noise. Experimental results with normalized least mean square (NLMS) adaptive algorithm demonstrate that the proposed method improves the perceived speech quality quite well besides the signal-to-noise ratio.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.9
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• pp.265-273
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• 2018

In this paper, we propose an acoustic event detection method in tunnels using non-negative tensor factorization (NTF) and hidden Markov model (HMM) applied to multi-channel audio signals. Incidents in tunnel are inherent to the system and occur unavoidably with known probability. Incidents can easily happen minor accidents and extend right through to major disaster. Most incident detection systems deploy visual incident detection (VID) systems that often cause false alarms due to various constraints such as night obstacles and a limit of viewing angle. To this end, the proposed method first tries to separate and detect every acoustic event, which is assumed to be an in-tunnel incident, from noisy acoustic signals by using an NTF technique. Then, maximum likelihood estimation using Gaussian mixture model (GMM)-HMMs is carried out to verify whether or not each detected event is an actual incident. Performance evaluation shows that the proposed method operates in real time and achieves high detection accuracy under simulated tunnel conditions.