• 한국통신학회논문지
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• 제36권12C호
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• pp.753-758
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• 2011

The constant modulus algorithm (CMA) widely used in blind equalization applications minimizes the averaged power of constant modulus error (CME) defined as the difference between an instant output power and a constant modulus. In this paper, a decision feedback version of the linear blind algorithm based on maximization of the zero-error probability for CME is proposed. The Gaussian kernel of the maximum zero-error criterion is analyzed to have the property to cut out excessive CMEs that may be induced from severely distorted channel characteristics. Decision feedback approach to the maximum zero-error criterion for CME is developed based on the characteristic that the Gaussian kernel suppresses the outliers and this prevents error propagation to some extent. Compared to the linear algorithm based on maximum zero-error probability for CME in the simulation of blind equalization environments, the proposed decision feedback version has superior performance enhancement particularly in cases of severe channel distortions.

• 한국통신학회논문지
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• 제34권2A호
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• pp.85-90
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• 2009

In this paper, as an alternative to constant modulus algorithm based on MSE, maximization of the probability that equalizer output power is equal to the constant modulus of the transmitted symbols is introduced. The proposed algorithm using the gradient ascent method to the maximum probability criterion has superior convergence and steady-state MSE performance, and the error samples of the proposed algorithm exhibit more concentrated density functions in blind equalization environments. Simulation results indicate that the proposed training has a potential advantage versus MSE training for the constant modulus approach to blind equalization.

• 한국정보전자통신기술학회논문지
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• 제9권2호
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• pp.190-195
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• 2016

본 연구에서는 균일 선형 배열 안테나 시스템에서 입사신호의 방향을 추정하기 위한 기존의 방법과 제안방법의 성능에 대해서 비교한다. 본 논문에서 제안한 방법은 최대 사후 확률 추정기를 적용하여 신호의 도래방향 추정 오차확률을 감소하고자 한다. 신호 추정 방향 확률 오차를 감소시키면 안테나에 입사하는 신호의 방향을 정확히 추정할 수 있다. 모의실험을 이용하여 본 연구에서 제안한 방법과 기존의 방법을 비교 분석하였으며 또한 배열 안테나 개수를 증가시키면서 신호 추정 오차 확률을 비교 분석하였다. 본 연구에서 제안한 방법이 기존의 방법보다 약 8%의 신호 추정 오차 확률을 감소시켜 도래방향 신호 추정 능력이 우수함을 입증하였다.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.535-545
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• 2015

In a various range of applications including hydrology, the type-I extreme value distribution has been extensively used as a probabilistic model for analyzing extreme events. In this paper, we introduce methods for estimating the scale parameter of the type-I extreme value distribution. A simulation study is performed to compare the estimators in terms of mean-squared error and bias, and the obtained results are provided.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1991년도 춘계학술대회
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• pp.65-70
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• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

• Journal of Communications and Networks
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• 제18권1호
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• pp.19-26
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• 2016

In this paper, the performance of dual-hop multi-relay maximum ratio transmission (MRT) over Rayleigh flat fading channels is studied with both conventional (all relays participate the transmission) and opportunistic (best relay is selected to maximize the received signal-to-noise ratio (SNR)) relaying. Performance analysis starts with the derivation of the probability density function, cumulative distribution function and moment generating function of the SNR. Then, both approximate and asymptotic expressions of symbol error rate (SER) and outage probability are derived for arbitrary numbers of antennas and relays. With the help of asymptotic SER and outage probability, diversity and array gains are obtained. In addition, impact of imperfect channel estimations is investigated and optimum power allocation factors for source and relay are calculated. Our analytical findings are validated by numerical examples which indicate that multi-relay MRT can be a low complexity and reliable option in cooperative networks.

• 한국산학기술학회논문지
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• 제16권3호
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• pp.2172-2177
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• 2015

상수 모듈러스 오차의 확률을 영으로 줄이는 등화 알고리듬에 결정 궤환 방식이 도입된 DF-MZEP-CME (decision feedback - maximum zero-error probability for constant modulus errors) 알고리듬은 채널 왜곡 보상에서 보다 향상된 성능을 보인다. 그러나 이 DF-MZEP-CME 알고리듬은 기울기 계산에서 샘플 사이즈에 비례하는 계산량을 가지게 되어 구현상 장애요인으로 작용한다. 이 논문에서는 DF-MZEP-CME 알고리듬의 기울기를 반복적으로 추정하도록 하여 계산량이 샘플 사이즈와 무관하게 함으로서 계산량 문제를 해결한다. 샘플 사이즈 N 에 대해 기존 알고리듬이 10N 의 곱셈량을 가지지만 제안한 방식은 샘플 사이즈와 무관하게 단지 20 번의 곱셈을 수행한다. 또한 제안한 방식의 기울기 계산이 초기상태로부터 안정 상태로 넘어갈 때 연속성을 유지하는 것으로 나타나 오차 전파에 예민한 결정 궤환 방식에 매우 적합한 알고리듬으로 판단된다.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.1-9
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• 2007

A three-state Markov logistic regression model is suggested to forecast the probability of tomorrow's precipitation based on the current meteorological situation. The suggested model turns out to be better than Markov regression model in the sense of the mean squared error of forecasting for the rainfall data of Seoul area.

• 한국통신학회논문지
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• 제39A권5호
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• pp.237-243
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• 2014

이 논문에서는, 영확률을 최대화 (maximum zero-error probability, MZEP) 하도록 설계된 알고리듬에서 가중치 갱신에 쓰이는 기존의 블록 처리 방식의 합산 연산을 대신하여, 다음 기울기 계산에 현재 계산된 기울기를 활용할 수 있는 효율적인 가중치 갱신 계산 방식을 제안하였다. 실험 결과로부터, 제안한 방식은 원래의 MZEP 와 동일한 성능을 나타내면서도 오차 버퍼가 불필요하여 시스템의 복잡도를 감소시키며 연산 시간을 현저히 줄일 수 있다. 또한 제안한 알고리듬은 오차 엔트로피 (error-entropy)를 최소화하도록 설계된 알고리듬보다 우수한 수렴 속도를 지닌다.

• 한국산업정보학회논문지
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• 제2권2호
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• pp.219-228
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• 1997

The Fano metric is the maximum likelihood decoding choice for convlutional code for binary symmetric channel. The Fano metric assumes that it has previous knowledge of channel error probability. However, the bit errors in real channel occur in bursts and the channel error probability can not be known exactly. Thus, the Fano metric is not the maximum likelihood choice for bursty-noise channel. In this paper universal metri which dose not require the previous knowlege of the channel transition probability is used for sequential decoding. It is shown that the complexity of the universal is much less than that of the Fano metric bursty-noise channel, since it is estimated on a branch by branch basis.