• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.3001-3011
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• 1996

In this paper, using DBNN algorithm which is used in the binary pattern classification or speech signal processing the digital DBNN circuit is designed having the variable expansion depending the size of input data and pattern type. The processing elemen(PE) of the proposed network consists of the synapse and MAXNET circuits for the similarity measurement between reference and input pattern. Global MAXNET selects the global winner among the local winners which is selected in each PE. Through the several simultions, and thus each PE and global MAXNET search the reference pattern that was the most simlar to input pattern for the discord of the pattern.

• Journal of Communications and Networks
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• v.3 no.4
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• pp.374-382
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• 2001

Nowadays, the commonly used table lookup scheme for IP routing is based on the sc-called classless interdomain routing (CIDR). With CIDR, routers must find out the best matching prefix (BMP) for IP packets forwarding, this complicates the IP lookup. Currently, this process is mainly performed in software and several schemes hale been proposed for hardware implementation. Since the IP lookup performance is a major design issue for the new generation routers, in this article we investigate the properties of the routing table and present a new approach for IP lookups, our approach is not based Gn BMP and significantly reduces the complexity, thus the computation cast of existing schemes can be significantly reduced. We also propose an efficient IP lookup algorithm, with which we improve the binary search on prefixes to 30 millions of packets per second (MPPS) and 5,000 route updates/s under the same experiment setup with an even larger routing table.

• Proceedings of the KAIS Fall Conference
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• 2004.11a
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• pp.137-140
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• 2004

RFID는 각종 서비스 산업은 물론 물류, 산업 현장, 제조 공장과 물품의 흐름이 있는 곳이면 어디에서나 적용이 가능하여 사회 여러 분야로부터 큰 관심을 받고 있다. 하지만 현재 900Mhz 대역의 RFID에서 사용하는 ISO18000-6의 프로토콜에서는 에러검출을 위한 CRC16만을 사용하여, 에러정정능력을 갖추지 못해 그 신뢰성이 떨어질 것으로 여겨진다. 본 논문에서는 이러한 RFID 시스템의 신뢰성 향상을 위해 Reader에서 Tag로의 Command data 전송 시에 대역확산방식과 콘벌루션부호를 적용하여 시스템의 신뢰성 향상을 목적으로 하며, 이러한 방식을 적용했을 때와 적용하지 않았을 때의 에러 율을 측정 비교하였다.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.665-670
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• 2003

In the applications like automatic masks generation for semiconductor production, a drawing consists of lots of polygons that are partitioned into trapezoids. The addition/deletion of a polygon to/from the drawing is performed through geometric operations such as insertion, deletion, and search of trapezoids. Depending on partitioning algorithm being used, a polygon can be partitioned differently in terms of shape, size, and so on. So, It's necessary to invent some comparison algorithm of sets of trapezoids in which each set represents interested parts of a drawing. This comparison algorithm, for example, may be used to verify a software program handling geometric objects consisted of trapezoids. In this paper, given k sets of trapezoids in which each set forms the regions of interest of each drawing, we present how to compare the k sets to see if all k sets represent the same geometric scene. When each input set has the same number n of trapezoids, the algorithm proposed has O(2$^{k-2}$ $n^2$(log n＋k)) time complexity. It is also shown that the algorithm suggested has the same time complexity O( $n^2$ log n) as the sweeping-based algorithm when the number k(<< n) of input sets is small. Furthermore, the proposed algorithm can be kn times faster than the sweeping-based algorithm when all the trapezoids in the k input sets are almost the same.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3286-3300
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• 2016

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4C
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• pp.253-261
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• 2005

In this paper, we propose an efficient block-based disparity estimation algorithm fur multiple view image coding in EE2 and EE3 in 3DAV. The proposed method emphasizes on visual quality improvement to satisfy the requirements for multiple view generation. Therefore, we perform an adaptive disparity estimation that constructs variable blocks by considering given image features. Examining neighboring features around desired block search range is set up to decrease complexity and additional information than only using quad-tree coding through applying binary-tree and quad-tree coding by taking into account stereo image feature having big disparity. The experimental results show that the proposed method improves PSNR about 1 to 2dB compared to existing other methods and decreases computational complexity up to maximum 68 percentages than FBMA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.509-517
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• 2001

Full-search algorithm requires large amount of computation which causes time delay or very complex hardware architecture for real time implementation. In this paper, we propose a fast motion estimator based on bit-plane matching, which reduce the computational complexity and the hardware cost. In the proposed motion estimator, the conventional motion estimation algorithms are applied to the binary images directly extracted from the video sequence. Furthermore, in the proposed VLSI motion estimator, we employ a Pair of processing cores that calculate the motion vector continuously By controlling the data flow in a systolic fashion using the internal shift registers in the processing cores, we avoid using SRAM (local memory) so that we remove the time overhead for accessing the local memory and adopt lower-cost fabrication technology. We modeled and tested the proposed motion estimator in VHDL, and then synthesized the whole system which has been integrated in a 0.6-$\mu$m triple-metal CMOS chip of size 8.15 X 10.84$\textrm{mm}^2$.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.562-569
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• 2019

Raman spectroscopy has been receiving increased attention as a standoff explosive detection technique. In addition, there is a growing need for a fast search method that can identify raman spectrum for measured chemical substances compared to known raman spectra in large database. By far the most simple and widely used method is to calculate and compare the Euclidean distance between the given spectrum and the spectra in a database. But it is non-trivial problem because of the inherent high dimensionality of the data. One of the most serious problems is the high computational complexity of searching for the closet spectra. To overcome this problem, we presented the MPS Sort with Sorted Variance+PDS method for the fast algorithm to search for the closet spectra in the last paper. the proposed algorithm uses two significant features of a vector, mean values and variance, to reject many unlikely spectra and save a great deal of computation time. In this paper, we present two new methods for the fast algorithm to search for the closet spectra. the PCA+PDS algorithm reduces the amount of computation by reducing the dimension of the data through PCA transformation with the same result as the distance calculation using the whole data. the Hierarchical Cluster Tree algorithm makes a binary hierarchical tree using PCA transformed spectra data. then it start searching from the clusters closest to the input spectrum and do not calculate many spectra that can not be candidates, which save a great deal of computation time. As the Experiment results, PCA+PDS shows about 60.06% performance improvement for the MPS Sort with Sorted Variance+PDS. also, Hierarchical Tree shows about 17.74% performance improvement for the PCA+PDS. The results obtained confirm the effectiveness of the proposed algorithm.

• Journal of Broadcast Engineering
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• v.16 no.5
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• pp.861-872
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• 2011

Many fast block-matching algorithms (BMAs) in motion estimation field reduce computational complexity by screening the number of checking points. Although many fast BMAs reduce computations, sometimes they should endure matching errors in comparison with full-search algorithm (FSA). In this paper, a novel fast BMA for constrained one-bit transform (C1BT)-based motion estimation is proposed in order to decrease the calculations of the block distortion measure. Unlike the classical fast BMAs, the proposed algorithm shows a new approach to reduce computations. It utilizes the binomial distribution based on the characteristic of binary plane which is composed of only two elements: 0 and 1. Experimental results show that the proposed algorithm keeps its peak signal-to-noise ratio (PSNR) performance very close to the FSA-C1BT while the computation complexity is reduced considerably.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2158-2165
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• 2007

In this paper, a Modified Fuzzy C-Means algorithm with Gaussian Weights(MFCM_GW) is presented for nonlinear blind channel equalization. The proposed algorithm searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function and Gaussian weighted partition matrix instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function(RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a simplex genetic algorithm(GA), a hybrid genetic algorithm(GA merged with simulated annealing(SA): GASA), and a previously developed version of MFCM. It is shown that a relatively high accuracy and fast search speed has been achieved.