• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.742-748
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• 2011

G-File on the position of the photo shoot pictures with built-in picture file to the user, the location and orientation of the image files using the data refers to the [1]. G-File is to store photo files, photo files and receiving means for receiving input, and picture files, photos and location information extracted by separating the subject's location information with location information and location analysis by means of the corresponding coordinates on the map including the location indicated in the guide means is characterized in that. In this paper, the G-File on the location information stored in the algorithm that can be managed is proposed. G-File on the algorithm used to manage the information to the user, G-File management is to provide convenience.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1009-1010
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• 2008

This paper presents a real-time aging measurement and feasible compensation system for the prolonged lifetime of OLED panel. The proposed system is composed of four parts, a PC with a man-machine interface, a measurement block, an adaptive amplifier block, and a compensation block. We apply a tree algorithm for less complexity and convenience of measurement on the degree of aging. An adaptive multi-stage differential amplifier is also implemented to deal with a various range of input voltages at the same spot.

• Journal of KIISE:Databases
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• v.32 no.5
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• pp.536-546
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• 2005

In this paper, we focus on the filtering step of candidate objects for spatial join operations on the input tables that none of the inputs is indexed. Over the last decade, several spatial Join algorithms for the input tables with index have been extensively studied. Those algorithms show excellent performance over most spatial data, while little research on solving the performance degradation in the presence of skewed data has been attempted. Therefore, we propose a spatial hash strip join(SHSJ) algorithm that can refine the problem of skewed data in the conventional spatial hash Join(SHJ) algorithm. The basic idea is similar to the conventional SHJ algorithm, but the differences are that bucket capacities are not limited while allocating data into buckets and SSSJ algorithm is applied to bucket join operations. Finally, as a result of experiment using Tiger/line data set, the performance of the spatial hash strip join operation was improved over existing SHJ algorithm and SSSJ algorithm.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.435-438
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• 2005

In this paper, we implemented a system that is called sound engine in musical synthesizer and synthesized a sound of Gayageum using TMS320C6713 DSK. Sound engine consists of two parts: synthesis algorithm and processor. We improved physical modeling using digital waveguide as a synthesis algorithm and we used TMS320C6713 as a processor. The excitation signals that make timbre are stored in memory. When we input parameters, sound engine synthesizes sound of Gayageum. The experimental result shows that synthesized sounds are very similar to real sounds.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.27-30
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• 2005

In this paper, we designed and manufactured the distortion cancellation module which is able to compensate thermal-noise distortion by software The distortion cancellation algorithm not only bring forth system non-linear distortion by input level but also bring compensate component of distortion by thermal to get rid off distortion from now on. After TMS320C6711 DSP to recognize our algorithm, we manufactured the module for every kinds of system To evaluate efficiency of the distortion cancellation module, we designed and manufactured communication system. By measured result, if system output power is -3dBm equally, 12dB of ACLR has improved in 1MHz away from a center frequency, and also gain has increased up to 0.5dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6A
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• pp.474-480
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• 2005

In this paper, we present a new scheduling scheme for MIMO OFDM Multiuser Diversity System. This scheduling scheme maximizes the system throughput, and at the same time fairly shares the resources based on the feedback information from the receivers and the queue information. To show the effectiveness of the proposed algorithm, we evaluate the performance of the proposed algorithm as compared to K&H and RR algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.10
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• pp.1865-1870
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• 2015

In signal processing, the zero-error probability (ZEP) criterion and related algorithm (MZEP) outperforms MSE-based algorithms and yields superior and stable convergence in impulsive noise environment. In this paper, the analysis of the relationship with MSE criterion proves that ZEP criterion has equivalent optimum solution of MSE criterion. Also this work reveals that the magnitude controlled input of MZEP algorithm plays the role in keeping the optimum solution undisturbed from impulsive noise.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.3
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• pp.1156-1173
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• 2021

In this paper, we propose a new joint precoder and postcoder design strategy to support multiple streams per user in multiuser multiple-input multiple-output (MIMO) systems. We propose two step precoding strategies using equal channel gain decomposition and block diagonalization at the transmitter. With the proposed precoder, the multiuser MIMO channel can be decomposed into multiple parallel channels with equal channel gain per user. After applying receive postcoder which is generated and sent by the transmitter, we can use ML based decoder per stream to achieve full receive diversity. Achievable sum rate bound and diversity performance of the proposed algorithm are presented with feedback signaling design and quantitative complexity analysis. Simulation results show that the proposed algorithm asymptotically approaches to the sum rate capacity of the MIMO broadcast channel while maintaining full diversity order.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12C
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• pp.1029-1034
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• 2010

For All Digital QPSK receivers, a phase recovery scheme is required to fix the arbitrarily rotated I/Q quadrature signals due to the transmission path and clock mismatch between the transmitter and the receiver. The conventional Costas phase recovery loop scheme requires a separate AGC(Automatic Gain Control) to obtain the performance independent of input signal power. This paper proposes a simple scheme which separates the phase and amplitude of the input signal via CORDIC algorithm and performs the phase recovery and amplitude compensation simultaneously. The proposed scheme can considerably reduce the logic resources in hardware implementation, has been verified by C++ and Model Sim simulations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2806-2825
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• 2018

Unsupervised learning has shown good performance on image, video and audio classification tasks, and much progress has been made so far. It studies how systems can learn to represent particular input patterns in a way that reflects the statistical structure of the overall collection of input patterns. Many promising deep learning systems are commonly trained by the greedy layerwise unsupervised learning manner. The performance of these deep learning architectures benefits from the unsupervised learning ability to disentangling the abstractions and picking out the useful features. However, the existing unsupervised learning algorithms are often difficult to train partly because of the requirement of extensive hyperparameters. The tuning of these hyperparameters is a laborious task that requires expert knowledge, rules of thumb or extensive search. In this paper, we propose a simple and effective unsupervised feature learning algorithm for image classification, which exploits an explicit optimizing way for population and lifetime sparsity. Firstly, a sparse target matrix is built by the competitive rules. Then, the sparse features are optimized by means of minimizing the Euclidean norm ($L_2$) error between the sparse target and the competitive layer outputs. Finally, a classifier is trained using the obtained sparse features. Experimental results show that the proposed method achieves good performance for image classification, and provides discriminative features that generalize well.