• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.2
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• pp.338-344
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• 1994

Price`s theorem is generalized for general zero memory nonlinear function when input are drawn from a sum, called the constrained non-Gaussian, of two or more mutually independent processes of which the first is the Gaussian. An example is given to illustrate the applicability of the generalization.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.418-422
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• 2013

This paper has considered the location estimation problem in two dimension space by using a non-linear filter under non-Gaussian noise in underwater acoustic sensor networks(UASNs). Recently, the extended Kalman filter (EKF) is widely used in location estimation. However, the EKF has a lot of problems in the non-linear system under the non-gaussian noise environment like underwater environment. In this paper, we propose the improved Two-Dimension Particle Filter (TDPF) using the re-interpretation distribution techniques based on the maximum likelihood (ML). Through the simulation, we compared and analyzed the proposed TDPF with the EKF under the non-Gaussian underwater sensor networks. Finally, we determined that the TDPF's result shows more accurate localization than EKF's result.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.5
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• pp.11-17
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• 2003

It is well known that the double integration of measured acceleration records is one of the most difficult signal processing, particularly in the measurements on civil engineering structures, The measured accelerations of civil engineering structures are usually non-stationary and contain non-gaussian low-frequency noises, which can be significant causes of numerical instabilities in double Integration, For the de-noising of this kind of signals, wavelet transform can be very effective because of its inherent processing features for non-stationary signals, In this paper, the de-noising algorithm for the double integration is proposed using the modified wavelet transform, which is extended version of ordinary wavelet transform to process non-gaussian and low-frequency noises, using the median filter concept, The example studies show that the integration can be improved by the proposed method.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1982.10a
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• pp.40-42
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• 1982

• Journal of Biomedical Engineering Research
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• v.22 no.2
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• pp.171-178
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• 2001

본 연구에서는 강건 시지연추정 알고리즘을 바탕으로 하여 표면근전도 신호로부터 새로운 근섬유 전도속도 측정방법을 제안하였다. 제시한 방법은 가우시안 가정 하에서 유도된 기존의 방법들로는 불가능한 비가우시안 충격성잡음을 포함하는 표면근전도 신호를 대상으로도 정확하게 근섬유 전도속도를 측정할 수 있다. 제시한 방법의 평가를 위하여 먼저, 마미총 증후군에 걸린 근질환자의 근전도 신호가 비가우시안 $\alpha$-stable 확률분포로 모델링할 수 있음을 보였으며, 정상인과 근질환자 6명의 피검자로부터 족저단신근과 내측광근에서 각각 근전도 신호를 수집하여 실험한 근섬유 전도속도 측정결과를 타 연구자들과 비교, 평가하였다. 실험결과, 족저단신근의 경우 근섬유 전도속도가 평균 4.60$\pm$0.50m/s로 내측광근의 경우 5.66$\pm$0.59m/s로 각각 구할 수 있었다.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.31-41
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• 2014

Biplot is a useful graphical method to simultaneously explore the rows and columns of a two-way data matrix. In particular, principal component factor biplot is a graphical method to describe the interrelationship among many variables in terms of a few underlying but unobservable random variables called factors. If we consider the unobservable variables (which are mutually independent and also non-Gaussian), we can apply the independent component analysis decomposing a mixture of non-Gaussian in its independent components. In this case, if we apply the principal component factor analysis, we cannot clearly describe the interrelationship among many variables. Therefore, in this study, we apply the independent component analysis of Jutten and Herault (1991) decomposing a mixture of non-Gaussian in its independent components. We suggest an independent component biplot to interpret the independent component analysis graphically.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.6
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• pp.1273-1280
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• 2013

The UKF algorithm for tracking moving objects has fast convergence speed and good tracking performance without the derivative computation. However, this algorithm has serious drawbacks which limit its use in conditions such as Gaussian noise distribution. Meanwhile, the particle filter(PF) is a state estimation method applied to nonlinear and non-Gaussian systems without these limitations. But this method also has some disadvantages such as computation increase as the number of particles rises. In this paper, we propose the Unscented Particle Filter (UPF) algorithm which combines Unscented Kalman Filter (UKF) and Particle Filter (PF) in order to overcome these drawbacks.The performance of the UPF algorithm was tested to compare with Particle Filter using a 2-DOF (Degree of Freedom) Pendulum System. The results show that the proposed algorithm is more suitable to the nonlinear and non-Gaussian state estimation compared with PF.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.7A
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• pp.522-527
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• 2012

In this paper, union upper bound on convolutional coded bit error rates (BER) is derived for downlink orthogonal frequency division multiple access (OFDMA) networks. According to the numerical results, for the small network loads, the BER performance with Laplacian decoding metric outperforms the BER performance with Gaussian decoding metric under downlink OFDMA networks with Viterbi decoder.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.04a
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• pp.176-177
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• 2000

대도시의 국소지역인 도심지 도로변 양측은 빌딩에 의해 둘러싸여 있어 canyon으로 비유되어 street canyon이라고 하며 도로에 관한 선행연구는 도로변에 관한 것과 street canyon에 관한 것 그리고 두 경우를 전부 포함하는 경우로 분류할 수 있다. 도로변에 있어서 자동차 배출가스의 확산 예측에 관한 연구는 가우시안형 해석해 모형이 가장 많고 그 외 비가우시안형 해석해 모형, 반경험식 모형, 수치해 모형으로 분류되고 있다. (중략)

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.9A
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• pp.1290-1298
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• 2000

Turbo Code decoder is an iterate decoding technology, which extracts extrinsic information from the bit to be decoded by calculating both forward and backward metrics, and uses the information to the next decoding step Turbo Code shows excellent performance, approaching Shannon Limit at the view of BER, when the size of Interleaver is big and iterate decoding is run enough. But it has the problems which are increased complexity and delay and difficulty of real-time processing due to Interleaver and iterate decoding. In this paper, it is analyzed that MAP(maximum a posteriori) algorithm which is used as one of Turbo Code decoding, and the factor which determines its performance. MAP algorithm proceeds iterate decoding by determining soft decision value through the environment and transition probability between all adjacent bits and received symbols. Therefore, to improve the performance of MAP algorithm, the trust between adjacent received symbols must be ensured. However, MAP algorithm itself, can not do any action for ensuring so the conclusion is that it is needed more algorithm, so to decrease iterate decoding. Consequently, MAP algorithm and Turbo Code performance are analyzed in the nongaussian channel applying Robust equalization technique in order to input more trusted information into MAP algorithm for the received symbols.