• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9A
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• pp.673-678
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• 2009

This paper presents a feedback method for improving the system capacity of MU-MIMO system for downlink channel environments. In a typical conventional feedback method, CVQ, in order to enhance the channel capacity, not only the feedback load is increased but also the quantization of the channel vector is increased, because the channel parameter of each user has to be fed back after quantizing one of the pre-defined N-codebook vectors. In this paper, a novel feedback method is proposed which provides an improved system capacity by transferring the channel state information without increasing the feedback load. Performance of the proposed method is compared to the conventional CVQ method through computer simulations. The simulation results show that the proposed method with 3-bit feedback provides a system capacity comparable to the CVQ method of 6-bit feedback when the number of transmit antennas is 2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.9
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• pp.721-727
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• 2012

Since a conventional multi-cell transmit diversity scheme depends on the feedback from the user for the channel gain information, its performance gets to severely degrade when the channel varies fast due to the high mobility of the user. Also, transmit power of the base station cannot be fully used in the conventional scheme because only one transmit antenna is used for data transmission. In this paper, we propose a multi-cell transmit diversity scheme appropriate for fast fading channel. In the proposed scheme, channel-independent precoding vector is applied over all transmit antennas and different precoding vectors are applied for neighboring subcarriers so that the received signal is avoided to experience deep fading over multiple neighboring subcarriers. Simulation results show that the proposed scheme has better detector output signal-to-noise ratio (SNR) and bit error rate (BER) performances than the conventional scheme.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.748-753
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• 2005

Among processes to manufacture parts from footwear materials like upper leathers, one of the most essential processes is the cutting one optimally arranging lots of parts on raw footwear materials and cutting. A new nesting strategy was proposed for the 2-dimensional part layout by using a two-stage approach, where which can be effectively used for water jet cutting. In the initial layout stage, a SOAL(Self-Organization Assisted Layout) based on the combination of FCM(Fuzzy C-Means) and SOM was adopted. In the layout improvement stage, SA(Simulated Annealing) based approach was adopted for a finer layout. The proposed approach saves much CPU time through a two-stage approach scheme, while other annealing-based algorithm so far reported fur a nesting problem are computationally expensive. The proposed nesting approach uses the stochastic process, and has a much higher possibility to obtain a global solution than the deterministic searching technique. We developed the automatic nesting software of NST(ver.1.1) software for footwear industry by implementing of these proposed algorithms. The NST software was applied by the optimized automatic arrangement algorithm to cut without the loss of leathers. if possible, after detecting damage areas. Also, NST software can consider about several features in not only natural loathers but artificial ones. Lastly, the NST software can reduce a required time to implement generation of NC code. cutting time, and waste of raw materials because the NST software automatically performs parts arrangement, cutting paths generation and finally NC code generation, which are needed much effect and time to generate them manually.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.9
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• pp.1682-1688
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• 2008

The Counterpropagation algorithm(CP) is a combination of Kohonen competition network as a hidden layer and the outstar structure of Grossberg as an output layer. CP has been used in many real applications for pattern matching, classification, data compression and statistical analysis since its learning speed is faster than other network models. However, due to the Kohonen layer's winner-takes-all strategy, it often causes instable learning and/or incorrect pattern classification when patterns are relatively diverse. Also, it is often criticized by the sensitivity of performance on the learning rate. In this paper, we propose an enhanced CP that has multiple Kohonen layers and dynamic controlling facility of learning rate using the frequency of winner neurons and the difference between input vector and the representative of winner neurons for stable learning and momentum learning for controlling weights of output links. A real world application experiment - pattern recognition from passport information - is designed for the performance evaluation of this enhanced CP and it shows that our proposed algorithm improves the conventional CP in learning and recognition performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.31-40
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• 2022

This paper proposes an augmented QSBC(Quantum Short-Block Code) that preserves the function of the existing QSBC and adds a single bit-flip error correction function due to Pauli X and Y errors. The augmented QSBC provides the diagnosis and automatic correction of a single Pauli X error by inserting additional auxiliary qubits and Toffoli gates as many as the number of information words into the existing QSBC. In this paper, the general expansion method of the augmented QSBC using seed vector and the realization method of the Toffoli gate of the single bit-flip error automatic correction function reflecting the scalability are also presented. The augmented QSBC proposed in this paper has a trade-off with a coding rate of at least 1/3 and at most 1/2 due to the insertion of auxiliary qubits.

• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.47-54
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• 2005

In the most of speaker recognition system, speaker's characteristics is extracted from acoustic parameter by speech analysis and we make speaker's reference pattern. Parameters used in speaker recognition system are desirable expressing speaker's characteristics fully and being a few difference whenever it is spoken. Therefore we su99est following to solve this problem. This paper is proposed to use strong spectrum characteristic in non-noise circumstance and prosodic information in noise circumstance. In a stage of making code book, we make the number of data we need to combine spectrum characteristic and Prosodic information. We decide acceptance or rejection comparing test pattern and each model distance. As a result, we obtained more improved recognition rate than we use spectrum and prosodic information especially we obtained stational recognition rate in noise circumstance.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.2
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• pp.49-59
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• 2007

This paper is about an system which can perform automatic semantic annotation to actualize "Semantic Web." Since it is impossible to tag numerous documents manually in the web, it is necessary to gather large Korean web documents as training data, and extract features by using natural language techniques and a thesaurus. After doing these, we constructed concept classifiers through the SVM (support vector machine) teaming algorithm. According to the characteristics of Korean language, morphological analysis and syntax analysis were used in this system to extract feature information. Based on these analyses, the concept code is mapped with Kadokawa thesaurus, which made it possible to map similar words and phrase to one concept code, to make training vectors. This contributed to rise the recall of our system. Results of the experiment show the system has a some possibility of semantic annotation.

• The Journal of the Acoustical Society of Korea
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• v.10 no.4
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• pp.38-47
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• 1991

The frequency variation among speakers is one of problems in the speech recognition. This paper applies fuzzy theory to solve the variation problem of frequency features. Reference patterns are expressed by fuzzified patterns which are produced by the peak frequency and the peak energy extracted from codebooks which are generated from training words uttered by several speakers, as they should include common features of speech signals. Words are recognized by fuzzy inference which uses the certainty factor between the reference patterns and the test fuzzified patterns which are produced by the peak frequency and the peak energy extracted from the power spectrum of input speech signals. Practically, in computing the certainty factor, to reduce memory capacity and computation requirements we propose a new equation which calculates the improved certainty factor using only the difference between two fuzzy values. As a result of experiments to test this word recognition method by fuzzy interence with Korean digits, it is shown that this word recognition method using the new equation presented in this paper, can solve the variation problem of frequency features and that the memory capacity and computation requirements are reduced.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.34-43
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• 2010

Texture information plays an important role in object recognition and classification. To perform an accurate classification, the texture feature used in the classification must be highly discriminative. This paper presents a novel texture descriptor for texture-based image retrieval and its application in Computer-Aided Diagnosis (CAD) system for Emphysema classification. The texture descriptor is based on the combination of local surrounding neighborhood difference and centralized neighborhood difference and is named as Combined Neighborhood Difference (CND). The local differences of surrounding neighborhood difference and centralized neighborhood difference between pixels are compared and converted into binary codewords. Then binomial factor is assigned to the codewords in order to convert them into high discriminative unique values. The distribution of these unique values is computed and used as the texture feature vectors. The texture classification accuracies using Outex and Brodatz dataset show that CND achieves an average of 92.5%, whereas LBP, LND and Gabor filter achieve 89.3%, 90.7% and 83.6%, respectively. The implementations of CND in the computer-aided diagnosis of Emphysema is also presented in this paper.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.54-59
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• 2012

Multiple antenna transmission and reception, whose principal merits are significant increase in spectral efficiency and/or reduction in error rate, lose much of their effectiveness in high levels of interference from other cells. Incorporating the other cell interference into advanced signal processing at transmitter and receiver is one of the key challenges for cell boundary users in cellular system. Since receiver can obtain exact knowledge of interference channels more easily than transmitter, an interference-aware multiple antenna receiver that can significantly attenuate interferences is considered. Based on the receiver, codebook-based coordinated precoding schemes are proposed. According to the level of cooperation, centralized and distributed schemes are proposed. We verified by the simulation results that even the distributed schemes, which have same amount of feedback and no cooperation between cells, have performance gain compared to the conventional non-coordinated scheme.