• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1901-1904
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• 2002

A good performance on communication systems is obtained by decreasing the length of training sequence In the initial stage of adaptive equalization. This paper presents a new approach to accomplish this, with the use of a training adaptive equalizer. The approach is based on combining the training and tracking modes, in which the training equalizer is updated by the LMS algorithm with the training sequence and then updated by a blind algorithm. By computer simulations, it is shown that a class of the proposed equalizers provides better performance than the conventional training equalizer.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.7
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• pp.85-91
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• 2016

Typically, radar systems change the pulse repetition interval of their modulated signal in order to avoid detection. On the other hand the radar-signal detection system tries to detect the modulation pattern. The histogram or auto-correlation methods are usually used to detect the PRI pattern of the radar signal. However these methods tend to lost the sequence information of the PRI pulses. This paper proposes a PRI-sequence detection algorithm based on the finite-state machine that could detect not only the PRI pattern but also their sequence.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.288-300
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• 2006

In this paper, we consider a channel ordering problem that seeks to minimize the total interference in mobile radio networks. If a base station receives connection request from a mobile user, one of the empty channels that are fixed to the base station is assigned to the mobile user. Among several channels available, we can choose one that seems to make least interference with other channels assigned to adjacent base stations. However, a pair of channels that are not separated enough do not generate interference if both of them are not simultaneously used by mobile users. That is, interference between channels may vary depending on the channel assignment sequence for each base station and on the distribution of mobile users. To find a channel assignment sequence that seems to generate minimum interference, we develop an optimization model considering various scenarios of mobile user distribution. Simulation results show that channel assignment sequence determined by the scenario based optimization model significantly reduces the interference provided that scenarios and interference costs are properly generated.

• Journal of the Korea Society of Computer and Information
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• v.13 no.2
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• pp.113-119
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• 2008

The World Wide Web is a dynamic collection of pages that includes a huge number of hyperlinks and huge volumes of usage informations. The resulting growth in online information combined with the almost unstructured web data necessitates the development of powerful web data mining tools. Recently, a number of approaches have been developed for dealing with specific aspects of web usage mining for the purpose of automatically discovering user profiles. We analyze sequence data, such as web-logs, protein sequences, and retail transactions. In our approach, we propose the clustering algorithm for sequence data using rough set theory. We present a simple example and experimental results using a splice dataset and synthetic datasets.

• Journal of the Korean Mathematical Society
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• v.43 no.2
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• pp.373-382
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• 2006

In this paper, we prove that the topological entropy of a sequence of equi-continuous monotone maps $f_{1,\infty}={f_i}\;\infty\limits_{i=1}$on circles is $h(f_{1,\infty})={\frac{lim\;sup}{n{\rightarrow}\infty}}\;\frac 1 n \;log\;{\prod}\limits_{i=1}^n|deg\;f_i|$. As applications, we give the estimation of the entropies for some skew products on annular and torus. We also show that a diffeomorphism f on a smooth 2-dimensional closed manifold and its extension on the unit tangent bundle have the same entropy.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.42-46
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• 2009

Superimposed training (SIT) design for estimating of time-varying multipath channels is investigated for mobile orthogonal frequency division multiplexing (OFDM) systems. The design of optimum SIT consists of two parts: The optimal SIT sequence is derived by minimizing the channel estimates' mean square error (MSE); the optimal power allocation between training and information data is developed by maximizing the averaged signal to interference plus noise ratio (SINR) under the condition of equal powered paths. The theoretical analysis is verified by simulations. For the metric of the averaged SINR against signal to noise ratio (SNR), the theoretical result matches the simulation result perfectly. In contrast to an interpolated frequency-multiplexing training (FMT) scheme or an SIT scheme with random pilot sequence, the SIT scheme with proposed optimal sequence achieves higher SINR. The analytical solution of the optimal power allocation is demonstrated by the simulation as well.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.4
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• pp.219-225
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• 2013

This paper presents a method using Maximum-Likelihood Linear Regression (MLLR) adaptation to improve recognition performance of Limabeam algorithm for speech recognition using microphone array. From our investigation on Limabeam algorithm, we can see that the performance of filtering optimization depends strongly on the supporting optimal state sequence and this sequence is created by using Viterbi algorithm trained with HMM model. So we propose an approach using MLLR adaptation for the recognition of speech uttered in a new environment to obtain better optimal state sequence that support for the filtering parameters' optimal step. Experimental results show that the system embedded with MLLR adaptation presents the word correct recognition rate 2% higher than that of original calibrate Limabeam and also present 7% higher than that of Delay and Sum algorithm. The best recognition accuracy of 89.4% is obtained when we use 4 microphones with 5 utterances for adaptation.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.45-52
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• 2000

Genomic approach produces massive amount of data within a short time period, New high-throughput automatic sequencers can generate over a million nucleotide sequence information overnight. A typical DNA chip experiment produces tens of thousands expression information, not to mention the tens of megabyte image files, These data must be handled automatically by computer and stored in electronic database, Thus there is a need for systematic approach of data collection, processing, and analysis. DNA sequence information is translated into amino acid sequence and is analyzed for key motif related to its biological and/or biochemical function. Functional genomics will play a significant role in identifying novel drug targets and diagnostic markers for serious diseases. As an enabling technology for functional genomics, bioinformatics is in great need worldwide, In Korea, a new functional genomics project has been recently launched and it focuses on identi☞ing genes associated with cancers prevalent in Korea, namely gastric and hepatic cancers, This involves gene discovery by high throughput sequencing of cancer cDNA libraries, gene expression profiling by DNA microarray and proteomics, and SNP profiling in Korea patient population, Our bioinformatics team will support all these activities by collecting, processing and analyzing these data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.1
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• pp.91-101
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• 2017

API call sequence analysis is a kind of analysis using API call information extracted in target program. Compared to other techniques, this is advantageous as it can characterize the behavior of the target. However, existing API call sequence analysis has an issue of identifying same characteristics to different function during the analysis. To resolve the identification issue and improve performance of analysis, this study includes the method of API abstraction technique in addition to existing analysis. From there on, similarity between target programs is computed and clustered into similar types by applying LSH to abstracted API call sequence from analyzed target. Thus, this study can attribute in improving the accuracy of the malware analysis based on discovered information on the types of malware identified.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.6
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• pp.290-297
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• 2014

The synchronization of OFDM receiver is consisted of symbol timing offset(STO) estimation in time domain and carrier frequency offset(CFO) estimation in frequency domain. This paper proposes new algorithm for correcting the integer CFO after we have done correcting the STO and partial CFO. ICFO must be corrected, since the ICFO lead to degrade bit error rate(BER) of demodulation performance. The PN sequence has information which is subcarrier order since the modified PN sequence, length is same subcarrier, is used in this paper and is modulated each subcarrier by each chip. Thus the receiver track phase of PN sequence after FFTin order to find the subcarrier frequency offset. The proposed algorithm is faster and more simple than convenient methode as measuring carrier energy.