• Journal of the Korea Society of Computer and Information
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• v.8 no.4
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• pp.63-68
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• 2003

Almost the system are usually taken by means of shapes and positions of ridge's end-points and bifurcation in the fingerprint recognition. but we studied about recognition of polluted fingerprint by chain code ridges. the results and sequence of processing are summarized as follows. (1)Capture several kinds of polluted fingerprint image. (2)Preprocessing(median filtering for removing noises, local and global histogram equalization, dilation and erosion, thinning and remove pseudo image), (3)Rebuild ridge line after Least Square Processing, (4)Compute distribution of chain code vector, (5)The results are almost same values of each vector of preprocessed fingerprint images. From the results, we can surmised more successful fingerprints recognition system in combination with other system by singular points

• Journal of KIISE:Software and Applications
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• v.33 no.10
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• pp.886-895
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• 2006

Fingerprint classification reduces the number of matches required in automated fingerprint identification systems by categorizing fingerprints into a predefined class. Support vector machines (SVMs), widely used in pattern classification, have produced a high accuracy rate when performing fingerprint classification. In order to effectively apply SVMs to multi-class fingerprint classification systems, we propose a novel method in which SVMs are generated with the one-vs-all (OVA) scheme and dynamically ordered with $na{\ddot{i}}ve$ Bayes classifiers. More specifically, it uses representative fingerprint features such as the FingerCode, singularities and pseudo ridges to train the OVA SVMs and $na{\ddot{i}}ve$ Bayes classifiers. The proposed method has been validated on the NIST-4 database and produced a classification accuracy of 90.8% for 5-class classification. Especially, it has effectively managed tie problems usually occurred in applying OVA SVMs to multi-class classification.

• The Journal of the Convergence on Culture Technology
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• v.5 no.1
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• pp.395-399
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• 2019

In order to support various parallel computing systems, it is necessary to extend LLVM IR to more efficiently support vector / matrix and to design LLVM IR to machine code as a new algorithm. As shown in the IR example, RISC instruction generation is naturally generated because the RISC instruction is basically composed of the RISC instruction, and the vector instruction is also not supported. There is a need for new IR structures, command generation algorithms and related extensions to support vector / matrix more robustly. To do this, it is important to map each instruction in the LLVM IR to the appropriate instruction in the target architecture (vector / matrix) (instruction selection algorithm). It is necessary to understand the meaning of LLVM IR command, to compare the meaning of each instruction of the target architecture with syntax, and to select the instruction that matches the pattern to make mapping efficient.

• Journal of Broadcast Engineering
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• v.15 no.3
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• pp.426-433
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• 2010

The H.264/AVC video coding standard performs inter prediction using variable block sizes to improve coding efficiency. Since we predict not only the motion of homogeneous regions but also the motion of non-homogeneous regions accurately using variable block sizes, we can reduce residual information effectively. However, each motion vector should be transmitted to the decoder. In low bit rate environments, motion vector information takes approximately 40% of the total bitstream. Thus, motion vector competition was proposed to reduce the amount of motion vector information. Since the size of the motion vector difference is reduced by motion vector competition, it requires only a small number of bits for motion vector information. However, we need to send the corresponding index of the best motion vector predictor for decoding. In this paper, we propose a new codeword table based on the phased-in code to encode the index of motion vector predictor efficiently. Experimental results show that the proposed algorithm reduces the average bit rate by 7.24% for similar PSNR values, and it improves the average image quality by 0.36dB at similar bit rates.

• Communications of Mathematical Education
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• v.6
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• pp.371-381
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• 1997

Let p be an odd prime number. We introduce simple and useful decoding algorithm for orthogonal Latin square codes of order p. Let H be the parity check matrix of orthogonal Latin square code. For any x ${\in}$ GF(p)$^{n}$, we call xH$^{T}$ the syndrome of x. This method is based on the syndrome decoding for linear codes. In L$_{p}$, we need to find the first and the second coordinates of codeword in order to correct the errored received vector.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.1
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• pp.96-102
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• 1995

This paper presents the VHSIC Hardware Description Language(VHDL) implementation of the Fixed Point Covariance Lattice(FLAT) algorithm for an Linear Predictive Coding(LPC) analysis and its related algorithms, such as the forth order high pass Infinite Impulse Response(IIR) filter, covariance matrix calculation, and Spectral Smoothing Technique(SST) in the Vector Sum Exited Linear Predictive(VSELP) speech coder that has been Selected as the standard speech coder for the North America and Japanese digital cellular. Existing Digital Signal Processor(DSP) chips used in digital cellular phones are derived from general purpose DSP chips, and thus, these DSP chips may not be optimal and effective architectures are to be designed for the above mentioned algorithms. Then we implemented the VHDL code based on the C code, Finally, we verified that VHDL results are the same as C code results for real speech data. The implemented VHDL code can be used for performing logic synthesis and for designing an LPC Application Specific Integrated Circuit(ASOC) chip and DsP chips. We first developed the C language code to investigate the correctness of algorithms and to compare C code results with VHDL code results block by block.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.65-66
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• 2008

A vector DLL represents signal tracking scheme utilizing navigation results, and it has been known that it has better performance than a conventional scalar DLL. This paper discusses the structure and conceptual benefits of the vector DLL, and describes implementation of the vector DLL in a software GPS receive. Also, the benefits of the vector DLL are confirmed by an experiment. Through the experiment, the code tracking accuracy between the vector DLL and a scalar DLL implementation is compared in static environments, and the navigation accuracy is analyzed using GPS signals received from a commercial GPS simulator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.10
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• pp.2634-2644
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• 1996

Two different low rate speech coders using one of four types of lattice vector quantizers(LVQ's) with fairly low complexity were investigated for an application to mobile communications. More specifically, two-stage vector quantizer-lattic vector quantizer(VQ-LVQ) systems and vector differenctial pulse code modulation(VDPCM)systems with lattice vector quantizers simulated to encode the line spectrum frequencies of various sentences at the rate 22 to 39 bits per 20 msec frame. The simulation results showed that the VDPCM system with the lattice VQ can save up to 10 bits/fram compared to the quantization scheme used in QCELP system. For the VQ-LVQ system, the spherical quasi-uniform LVQ below 36 bits/frame outperformed the other 3 types of LVQ's and the pyramidal quasi-uniform LVQ at 37 bits/frame outperformed the other 3 types of LVQ's with the spectral distortion 0.97.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.281-288
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• 2009

This paper proposes a novel algorithm for the efficient classification and annotation of medical images, especially X-ray images. Since X-ray images have a bright foreground against a dark background, we need to extract the different visual descriptors compare with general nature images. In this paper, a Color Structure Descriptor (CSD) based on Harris Corner Detector is only extracted from salient points, and an Edge Histogram Descriptor (EHD) used for a textual feature of image. These two feature vectors are then applied to a multi-class Support Vector Machine (SVM), respectively, to classify images into one of 20 categories. Finally, an image has the Annotation Code Array based on the pre-defined hierarchical relations of categories and priority code order, which is given the several optimal keywords by the Annotation Code Array. Our experiments show that our annotation results have better annotation performance when compared to other method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.8
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• pp.1383-1391
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• 2008

This paper presents an implementation of vector control for SPMSM using model based controller design in MATLAB/SIMULINK. The model based controller design enables fast development of control system for motor by designing controllers and performing simulation on the GUI (Graphic User Interface) platform, converting program code directly into real-time programs, and then performing tests for the responses from controllers. The controllers designed in this paper are PI speed controller and decoupling PI current controller. Also space vector modulation method using offset voltage is used in PWM scheme. And system stability is also secured by close magnitude overmodulation method, maintaining dynamics of load when overmodulation occurs. The validity of vector control implemented is verified through simulations and experiments.