• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.351-358
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• 2002

Video compression based on DCT (Discrete Cosine Transform) has weakpoints of blocking artifacts and pixel loss when the resolution is changed. DWT (Discrete Wavelet Transform) based method can overcome such problems. In SAMCoW (Scalable Adaptive Motion Compensation Wavelet), one of wavelet based video coding algorithm, both intra frames and motion compensated error frames are encoded using EZW(Embedded Zerotree Wavelet) algorithm. However the property of wavelets transform coefficients of motion compensated error frames are different from that of still images. Signal energy is not highly concentrated in the lower bands which is true for most still image cases. Signal energy is rather evenly distributed over all frequency bands. This paper suggests a new video coding algorithm utilizing these properties. Spatial band coding which is known to be very effective for encoding images with relative1y high frequency components and not utilizing the interband coefficients correlation is applied instead of EZW to encode both intra and inter frames. In spatial band coding, the position and value of significant wavelet coefficients in each band are progressively transmitted. Unlike EZW, inter band coefficients correlations are not utilized in spatial band coding. It has been shown that spatial band coding gives better performance than EZW when applied to wavelet based video compression.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.150-155
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• 2003

We discussed a quantitative structure-activity relationships (QSAR) technique on incomplete data set. We proposed a new solver that used 2 kinds of multi-layer neural networks. One is to compensate the defect data, and another is to evaluate the QSAR. The solver can predict the defects in model QSAR data. By using them, we get very high precision QSAR. It is 5-10 times higher than that of a traditional method. However, in case of anti-cancer Carboquone, the prediction is not so complete. It was about O(3) wrong than the model calculation. The predicted values would have rather large error. It is caused by noisy observations of Carboquone. However, if we used the uncertain predictions, new data are included in QSAR. If not, they were omitted. The effect would not be little. Therefore, we evaluated the QSAR. The results are contrary to the expectation, are not so wrong. We believe that the wrong effect is suppressed by including information of new data.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• JSTS:Journal of Semiconductor Technology and Science
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• v.6 no.4
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• pp.299-312
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• 2006

This paper presents the results of a novel test structure for process control monitor for uncooled IR detector technology of microbolometer arrays. The proposed test structure is based on resistive network configuration. The theoretical model for resistance of this network has been developed using 'Compensation' and 'Superposition' network theorems. The theoretical results of proposed resistive network have been verified by wired hardware testing as well as using an actual 16x16 networked bolometer array. The proposed structure uses simple two-level metal process and is easy to integrate with standard CMOS process line. The proposed structure can imitate the performance of actual fabricated version of area array closely and it uses only 32 pins instead of 512 using conventional method for a $16{\times}16$ array. Further, it has been demonstrated that the defective or faulty elements can be identified vividly using extraction matrix, whose values are quite similar(within the error of 0.1%), which verifies the algorithm in small variation case(${\sim}1%$ variation). For example, an element, intentionally damaged electrically, has been shown to have the difference magnitude much higher than rest of the elements(1.45 a.u. as compared to ${\sim}$ 0.25 a.u. of others), confirming that it is defective. Further, for the devices having non-uniformity ${\leq}$ 10%, both the actual non-uniformity and faults are predicted well. Finally, using our analysis, we have been able to grade(pass or fail) 60 actual devices based on quantitative estimation of non-uniformity ranging from ＜ 5% to ＞ 20%. Additionally, we have been able to identify the number of bad elements ranging from 0 to ＞ 15 in above devices.