• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.163-174
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• 2009

Applying the maximally polyphase decomposition and noble identity to the adaptive filter in subband structure, the conventional fullband affine projection algorithm is translated to the subband affine projection (SAP) algorithm. The Maximally polyphase decomposed SAP (MPDSAP) algorithm is a special version of the SAP algorithm, and its adaptive sub-filters have unity projection dimension. The weight updating formular of the MPDSAP is similar to that of the NLMS algorithm, so it may be more proper algorithm than other AP-type algorithms for many practical applications. This paper presents a new statistical analysis of the MPDSAP algorithm. The analytical model is derived for autoregressive (AR) inputs and the nonunity adaptive gain in the subband structure with the orthonormal analysis filters (OAF), The pre-whitening by the OAF allows the derivation of a simple-analytical model for the MPDSAP with the AR inputs and the nonunity adaptive gain.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.4
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• pp.391-397
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• 2003

This paper is about the digital image decimation algorithm which generates a value of decimated element by an average of a target pixel value and a value of neighbor intelligible element to adaptively reflect the merits of ZOD method and FOD method on the decimated image. First, a target pixel located at the center of sliding window is selected, then the gradient amplitudes of its right neighbor pixel and its lower neighbor pixel are calculated using first order derivative operator respectively. Secondly, each gradient amplitude is divided by the summation result of two gradient amplitudes to generate each intelligible weight. Next, a value of neighbor intelligible element is obtained by adding a value of the right neighbor pixel times its intelligible weight to a value of the lower neighbor pixel times its intelligible weight. The decimated image can be acquired by applying the process repetitively to all pixels in input image which generates the value of decimated element by calculating the average of the target pixel value and the value of neighbor intelligible element.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.49-54
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• 2017

Pathfinding for pedestrians provided by various navigation programs is based on a shortest path search algorithm. There is no big difference in their guide results, which makes the path quality more important. Multiple criteria should be included in the search cost to calculate the path quality, which is called a multi-criteria pathfinding. In this paper we propose a user adaptive pathfinding algorithm in which the cost function for a multi-criteria pathfinding is defined as a weighted sum of multiple criteria and the weights are learned automatically by Perceptron learning. Weight learning is implemented in two ways: short-term weight learning that reflects weight changes in real time as the user moves and long-term weight learning that updates the weights by the average value of the entire path after completing the movement. We use the weight update method with momentum for long-term weight learning, so that learning speed is improved and the learned weight can be stabilized. The proposed method is implemented as an app and is applied to various movement situations. The results show that customized pathfinding based on user preference can be obtained.

• Journal of Korean Academy of Nursing
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• v.13 no.3
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• pp.51-60
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• 1983

Currently changing trends of child health care is demand total health assessment of child including growth and development. This study concentrates on the growth & developmental status of low birth weight infant for help their growth & development. Thus it can be provide a direction for scientific health education and counseling materials by investigating factor of growth & development. The subjects for this study were made up of 40 low birth weight infant who attended the well baby clinic of E university Hospital. The study method used was a questionnaire ＆ anthropometric assessment and DDST for normative data of development. The period for data collection was from July 1st to August 31th, 1982. Analysis of the data was done using percentages, $\chi$$^2$-test Stepwise Multiple Regression. The results of study were as follows. 1. The mean weight of birth was 2,068gm and mean of gestational period was 35.65 weeks. 2. The age at which weight ; 32.5%, head circumference : 67,5% chest circumference : 55.0%, height : 50. 0％ was normal range of physical growth. 3. The reverse age at which social development ; 87.5%, fine motor & adaptive development ; 70.0%, gross motor development ; 72.5% of children Passed by DDST to determine of normal range of development. 4. In the among variables, it was found that the infant who were the higher emotional & verbal response of mother and stimulus environment was the more normal range of weight & development than who was not. 5. The stepwise Multiple Regression between developmental status and predictors-birth order, weight at birth, sex, antenatal care, gestational period-are accounts for 34.1%.

• The Journal of Information Technology
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• v.4 no.1
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• pp.71-79
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• 2001

This paper presents an adaptive back propagation algorithm that update the learning parameter by the generated error, adaptively and configuration of the range for the initial connecting weight according to the different maximum target value from minimum target value. This algorithm is expected to escaping from the local minimum and make the best environment for the convergence. On the simulation tested this algorithm on three learning pattern. The first was 3-parity problem learning, the second was $7{\times}5$ dot alphabetic font learning and the third was handwritten primitive strokes learning. In three examples, the probability of becoming trapped in local minimum was reduce. Furthermore, in the alphabetic font and handwritten primitive strokes learning, the neural network enhanced to loaming efficient about 27%~57.2% for the standard back propagation(SBP).

• ETRI Journal
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• v.20 no.2
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• pp.133-148
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• 1998

The objective of this paper is to present an adaptive algorithm for computing the weight vector which provides a beam pattern having its maximum gain along the direction of the mobile target signal source in the presence of interfering signals within a cell. The conjugate gradient method (CGM) is modified in such a way that the suboptimal weight vector is produced with the computational load of O(16N), which has been found to be small enough for the real-time processing of signals in most land mobile communications with the digital signal processor (DSP) off the shelf, where N denotes the number of antenna elements of the array. The adaptive procedure proposed in this paper is applied to code division multiple access (CDMA) mobile communication system to show its excellent performance in terms of signal to interference plus noise ratio (SINR), bit error rate (BER), and capacity, which are enhanced by about 7 dB, ${\frac{1}{100}}$ times, and 7 times, respectively, when the number of antenna elements is 6 and the processing gain is 20 dB.

• The Journal of the Acoustical Society of Korea
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• v.13 no.1E
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• pp.25-36
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• 1994

A problem of making a neural network learning self-adaptive to the training set supplied is addressed in this paper. This arises from the aspect in choice of an adequate stepsize for the update of the current weigh vectors according to the training pairs. Related issues in this attempt are raised and fundamentals in neural network learning are introduced. In comparison to the most popular back-propagation scheme, the usefulness and superiority of the proposed weight update algorithm are illustrated by examing the identification of unknown nonlinear systems only from measurements.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.844-847
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• 2003

Display devices are becoming increasingly important as an interface between humans and machines in the growing information society. In display devices, PDP (Plasma Display Panel) has many advantages in that it has wide screen, wide viewing angle and is light weight, thin. In PDP driving method, if the brightness of input image is high, applying the fixed sustain pulse to the PDP panel will raise the PDP power consumption and may damages the PDP panel. To overcome these problems, the Plasma AI driving method was introduced by the Matshushita co. in Japan. The Plasma AI driving module calculates the peak value and average value of 1 frame image and adjusts the gradation and sustain pulses for 1 frame sustain. In this paper, the proposed PDP driving module is based on the Plasma AI driving module. The proposed driving module calculates peak value and average value, and the brightness distribution of 1 frame image. Using brightness distribution, the proposed driving module divides 1 frame input image into 15 image patterns. For each image pattern, minimum sustain pulses and sub-frames are used for the brightness of 1 frame image and the sustain weight for 64, 128, 192 gradation is proposed. Therefore, the sustain power consumption can be reduced.

• Transactions of the Korean Society of Mechanical Engineers
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• v.11 no.2
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• pp.234-242
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• 1987

The solution of shape design problems based on variational analysis has been approached by using the domain adaptive method. The objective of the structural shape design is to minimize the weight within a bound on local stress measure, or to minimize the maximum local stress measure within a bound on the weight. A derived optimality condition in both design problems requires that the unit mutual energy has constant value along the design boundary. However, the condition for constant stress on the design boundary was used in computation since the computed mutual energy oscillates severely on the boundary. A two step iteration scheme using domain adaptation was presented as a computational method to slove the example designs of elastic structures. It was also shown that remeshing by grid adaptation was effective to reduce oscillatory behavior on the design boundary.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.1
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• pp.305-326
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• 2019

Discriminative correlation filter (DCF) based tracking algorithms have recently shown impressive performance on benchmark datasets. However, amount of recent researches are vulnerable to heavy occlusions, irregular deformations and so on. In this paper, we intend to solve these problems and handle the contradiction between accuracy and real-time in the framework of tracking-by-detection. Firstly, we propose an innovative strategy to combine the template and color-based models instead of a simple linear superposition and rely on the strengths of both to promote the accuracy. Secondly, to enhance the discriminative power of the learned template model, the spatial regularization is introduced in the learning stage to penalize the objective boundary information corresponding to features in the background. Thirdly, we utilize a discriminative multi-scale estimate method to solve the problem of scale variations. Finally, we research strategies to limit the computational complexity of our tracker. Abundant experiments demonstrate that our tracker performs superiorly against several advanced algorithms on both the OTB2013 and OTB2015 datasets while maintaining the high frame rates.