• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.12
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• pp.1013-1020
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• 2013

In this paper the super-resolution time delay estimation algorithms based on eigen-analysis are developed for spread spectrum signals along with their comparative performance analysis. First, we shall develop super-resolution time delay estimation algorithms using the representative eigen-analysis based AOA (angle-of-arrival) estimation algorithms such as MUSIC, Minimum-Norm, and ESPRIT, and apply them to the ISO/IEC 24730-2.1 real-time locating system (RTLS) employing a direct sequence spread spectrum (DS-SS) technique to compare their performances in RTLS environments. Simulation results illustrate that all the three algorithms can resolve multipath signals whose delay differences are even smaller than the Rayleigh resolution limit. Simulation results also show that MUSIC and Minimum-Norm provide a similar performance while ESPRIT is inferior to both algorithms in RTLS environments.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.24-29
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• 1993

In this paper, the estimation of the structure of a logic circuit under test is made from the observation of the input-output correlation function by use of M-sequence, from which we can estimate whether or not any fault exist in the logic circuit. Especially, investigation was made in case of the 2_stage logic circuit. We checked theoretically the sequence of correlation function, and we have shown that the correlation function is a function of period of M-sequence only, land the appearing number of correlation function in a period is a constant value depending on the logic circuit only. And by computer simulations we have shown that the structure of the circuit under test can be estimated from the observation of sequence of correlation function.

• Journal of the Korean housing association
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• v.12 no.3
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• pp.109-116
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• 2001

Street is an important factor that street quality determines urban quality as the space of the high public nature in city. The research method considering sequence landscape is important because it is considered that the impression of such a street is formed by the wholeness of consecutive landscape and experience in moving street. Therefore, this study are pursued to structure the analysis of psychological evaluation and environmental attribute base on the physical characteristics of sequence landscape to supply the basic materials for seeking the national direction as qualitative improvement of urban street space and the attractive urban street space. Then the results are as follows. It is shown that the psychological evaluation structure of sequence landscape is evaluated by ornamental nature, intimacy, orderliness, openness and movability and that of environmental attributes is evaluated by four factors such as activity, intimacy, spatial attribute and openness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.2A
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• pp.169-178
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• 2007

In this paper, we propose a signal structure and its optimum receiver to improve performance of SC-FDE(Single Carrier with Frequency Domain Equalization) system. Conventional SC-FDE systems have a drawback of power unbalance in frequency domain due to generation of pilot signals in time domain. The unbalanced power in frequency domain induces a channel estimation error and the performance of the receiver is degraded significantly. To overcome the drawback we apply CAZAC sequence which has constant power distribution in time and frequency domain. We design the signal structure to improve the performance with the repeated CAZAC sequence, and we design a receiver to optimize the proposed structure. Computer simulation results show that the proposed structure is superior to the conventional structure considering frame synchronization, frequency synchronization and channel equalization on typical wireless mobile channel environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5A
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• pp.479-486
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• 2008

In this paper, an efficient training symbol design with m-sequence is proposed for the MIMO-OFDM based next generation wireless transmission system which supports gigabits per second data rate. In the traditional blute force method, the preamble design is based on the case by case comparison with the system requirements. This paper discusses a training symbol design methodology for the MIMO-OFDM system based on the m-sequence which has been widely used in the spread spectrum communication areas due to its good correlation characteristics. Also the step-by-step design and performance verification method within the limited search space is discussed. The proposed method targets the design of the training symbol which satisfies system requirements for the packet based MIMO-OFDM wireless communication system including automatic gain control(AGC), timing synchronization, frequency and sampling offset estimation, and MIMO channel estimation.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1839-1845
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• 2016

Detecting remote targets is important to active protection system (APS) or infrared search and track (IRST) applications. In normal situation, the well-known constant false alarm rate (CFAR) detector works properly. However, decoys in APS or closely spaced targets in IRST degrade the detection capability by increasing background noise level in the CFAR detector. This paper presents a context aware CFAR detector by the intensity sorting and selection of background region to reduce the effect of neighboring targets that lead to incorrect estimation of background statistics. The existence of neighboring targets can be recognized by intensity sorting where neighboring targets usually show highest ranks. The proposed background statistics (mean, standard deviation) estimation method from median local pixels can be aware of the background context and reduce the effects of the neighboring targets, which increase the signal-to-clutter ratio. The experimental results on the synthetic APS sequence, real adjacent target sequence, and remote pedestrian sequence validated that the proposed method produced an enhanced detection rate with the same false alarm rate compared with the hysteresis-CFAR (H-CFAR) detection.

• Journal of Korea Multimedia Society
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• v.1 no.1
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• pp.109-119
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• 1998

This paper describes a research result on automatic generation of Abstract Test Suite from INAP protocol in formal specifications by applying many existing related algorithms such as Rural Chinese Postman Tour and UIO sequence concepts. We use the I/O FSM generated from SDL specifications and a characterizing sequence concepts. We use the I/O FSM generated from SDL specifications and a characterizing sequence, called UIO sequence, is defined for the I/O FSM. The UIO sequence is combined with the concept of Rural Chinese Postman tour to obtain an optimal test sequence. It also proposes an estimation methodology of the fault courage for the Test Suite obtained by our method and their translation into the standardized test notation TTCN.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.147-150
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• 2004

In this paper, we propose a reduced-state sequence estimation (RSSE) for trellis coded modulation (TCM) in OFDM with two-stage IDFT/ DFTs, MMSE-LE, and interleaving on frequency selective Rayleigh fading channels. The Viterbi algorithm (VA) is used to search for the best path through the reduced-state trellis combined with equalization and TCM decoding. Computer simulations confirm the bit error probability of the proposed scheme.

• Journal of the Korean Statistical Society
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• v.24 no.1
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• pp.149-160
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• 1995

We consider the problem of optimal adaptive estiamtion of the euclidean parameter vector $\theta$ of the univariate non-linerar autogressive time series model ${X_t}$ which is defined by the following system of stochastic difference equations ; $X_t = \sum^p_{i=1} \theta_i \cdot T_i(X_{t-1})+e_t, t=1, \cdots, n$, where $\theta$ is the unknown parameter vector which descrives the deterministic dynamics of the stochastic process ${X_t}$ and ${e_t}$ is the sequence of white noises with unknown density $f(\cdot)$. Under some general growth conditions on $T_i(\cdot)$ which guarantee ergodicity of the process, we construct a sequence of adaptive estimatros which is locally asymptotic minimax (LAM) efficient and also attains the least possible covariance matrix among all regular estimators for arbitrary symmetric density.