• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1032-1036
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• 2006

본 연구에서는 영산강 본류를 대표하는 나주지점을 대상으로 하여, 해당 지점에서 자동 측정되고 있는 수질 항목들 중에서 총유기탄소(TOC: Total Organic Carbon)의 시계열 자료에 대한 비선형 동역학적 거동을 파악하고자 하였다. 1994년 낙동강에서의 수질오염 사고 이후 4대강 유역에서 설치.운영되고 있는 수질자동 측정망의 TOC 자료를 일자료로 환산하여 사용하였으며, 시계열 자료에 비선형 동역학적(카오스적) 특성이 존재하는지를 알아보기에 앞서 자료의 전처리 과정으로써 3가지의 잡음제거 방법을 적용하였다. 잡음이 제거된 시계열 자료에 비선형 동역학적 거동의 파악을 위해 보편적으로 사용되고 있는 상관차원분석을 실시하였다. 또한 상관차원분석 결과 비선형 동역학적 거동을 나타내는 것으로 판별된 자료에 대하여 그 양상을 가시적으로 알아보기 위해 지체시간$(\tau)$을 적용하여 3차원 위상공간에 도시하였다. 본 연구의 결과, 나주지점에서 측정되고 있는 총유기탄소에 대해 비선형 잡음제거 방법을 적용한 자료가 비선형 동역학적 거동을 내재하고 있는 것으로 나타났으나, 이를 위상공간에 재건하였을 경우 이상한 끌개(strange attractor)의 뚜렷한 구조가 보이지 않았다. 그러나 상관차원분석 결과 잡음이 제거된 자료가 카오스적 특성을 보이므로, 자료의 단기예측을 위한 방법에 기초적인 정보를 제공할 수 있을 것으로 기대된다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.10
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• pp.2280-2286
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• 2012

In this paper, we propose a novel nonlinear 3D image correlator using a fast computational integral imaging reconstruction (CIIR) method. In order to implement the fast CIIR method, the magnification process was eliminated. In the proposed correlator, elemental images of the reference and target objects are picked up by lenslet arrays. Using these elemental images, reference and target plane images are reconstructed on the output plane by means of the proposed fast CIIR method. Then, through nonlinear cross-correlations between the reconstructed reference and the target plane images, the pattern recognition can be performed from the correlation outputs. Nonlinear correlation operation can improve the recognition of 3D objects. To show the feasibility of the proposed method, some preliminary experiments are carried out and the results are presented by comparing the conventional method.

• Korean Journal of Optics and Photonics
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• v.1 no.2
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• pp.130-134
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• 1990

In this paper, pSDF-based referance image is reahzed. Using BJTC(binary joint transform correlator) as nonlinear correlator, optical pattern recognition for interclass discrimination is performed. Experimental results show that correlation peak intensity of one calss is two times higher than that of the other class, which indicates its superiority in discrimination sensitivity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.712-717
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• 2013

In this paper, we propose a performance-enhanced object recognition by using nonlinear 3D correlator based on pixel restoration. In the proposed method, elemental images of the 3D target that are partially occluded by a foreground object are picked up and transformed into sub-images. By using the block-matching algorithm, the occluded target regions of each sub-image are estimated and removed. After that, the missing pixels in each sub-image are reestablished by using the pixel-restoration method. Finally, through the nonlinear cross-correlations between the reconstructed reference and the target plane images, the improved object recognition can be performed. To show the feasibility of the proposed method, some preliminary experiments are carried out and results are presented by comparing the conventional method.

• The Journal of the Korea Contents Association
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• v.3 no.3
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• pp.98-102
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• 2003

For elucidating the key role of hidden neurons in information processing of Multilayer perceptrons(MLPs), we prove that the correlation coefficient between weighted sums to hidden neurons decreases under element-wise nonlinear transformations. This is verified through training of MLPs for an isolated word recognition problem. From this result, we can say that the element-wise nonlinear functions reduces redundancy in the information contents of hidden neurons.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.1
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• pp.190-196
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• 2013

Curved integral imaging is a simple method to display 3D images in space using lens array and provides wide viewing angle. In this paper, we propose a nonlinear 3D correlator based on the direct pixel-mapping (DPM) method in order to improve the recognition performance of 3D target object in curving-effective integral imaging. With this scheme, the elemental image array (EIA) originally picked up from a partially occluded 3-D target object can be converted into a resolution enhanced new EIA by using DPM method. Then, through nonlinear cross-correlations between the reconstructed reference and the target plane images, the improved pattern recognition can be performed from the correlation outputs. To show the feasibility of the proposed method, some preliminary experiments are carried out and results are presented by comparing the conventional method.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.731-740
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• 1999

Autocorrelation function is widely used as a tool measuring linear dependence of hydrologic time series. However, it may not be appropriate for choosing decorrelation time or delay time ${\tau}_d$ which is essential in nonlinear dynamics domain and the mutual information have recommended for measuring nonlinear dependence of time series. Furthermore, some researchers have suggested that one should not choose a fixed delay time ${\tau}_d$ but, rather, one should choose an appropriate value for the delay time window ${\tau}_d={\tau}(m-1)$, which is the total time spanned by the components of each embedded point for the analysis of chaotic dynamics. Unfortunately, the delay time window cannot be estimated using the autocorrelation function or the mutual information. Basically, the delay time window is the optimal time for independence of time series and the delay time is the first locally optimal time. In this study, we estimate general dependence of hydrologic time series using the C-C method which can estimate both the delay time and the delay time window and the results may give us whether hydrologic time series depends on its linear or nonlinear characteristics which are very important for modeling and forecasting of underlying system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.4
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• pp.730-736
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• 2012

PN(Pseudo Noise) sequences play an important role in wireless communications, such as in a CDMA(code division multiple access) communication system. If there is a crash when multiple users simultaneously connected to a system, then PN sequences with low correlation help to minimize multiple access interference in such communication system. In this paper we propose a family of non-linear extended binary sequences with low cross-correlations and the family include $m$-sequence, GMW sequence, Kasami sequence and No sequence with optimal cross-correlation in terms of Welch bound. And we analyze cross-correlation of these sequences.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.8
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• pp.1686-1692
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• 2012

Spreading sequence play an important role in wireless communications, such as in a CDMA(code division multiple access) communication system and multi-carrier spectrum communication system. Spreading sequences with low cross-correlation, in a direct-sequence spread spectrum communication system, help to minimize multiple access interference and to increase security degree of system. Analysis of cross-correlations between the sequences is a necessary process to design sequences. However it require lots of computing time for analysis of cross-correlations between sequences. In this paper we propose a method which is possible to compute effectively cross-correlation using subfield in the process of practical computation of cross-correlation between nonlinear binary sequences.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.5
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• pp.555-562
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• 2012

This paper presents a hybrid method for improving the recognition performance, which is based on the nonlinear histogram equalization, features extraction, and statistical correlation of images. The nonlinear histogram equalization based on a logistic function is applied to adaptively improve the quality by adjusting the brightness of the image according to its intensity level frequency. The statistical correlation that is measured by the normalized cross-correlation(NCC) coefficient, is applied to rapidly and accurately express the similarity between the images. The local features based on independent component analysis(ICA) that is used to calculate the NCC, is also applied to statistically measure the correct similarity in each images. The proposed method has been applied to the problem for recognizing the 30-face images of 40*50 pixels. The experimental results show that the proposed method has a superior recognition performances to the method without performing the preprocessing, or the methods of conventional and adaptively modified histogram equalization, respectively.