• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.35-36
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• 2012

The generation of fuzzy rules is inevitable in order to construct fuzzy modeling and in general, has the problem that the number of rules increases exponentially with increasing dimension. To solve this problem, we introduce the system that generate the fuzzy rules and make a inference based on FCM clustering algorithm that partition the input space in the scatter form. The parameters in the premise part of the fuzzy rules is determined as membership matrix by the FCM clustering algorithm and the consequence part of the fuzzy rules is are expressed as a polynomial function. Proposed model evaluated using the numerical data.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.4
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• pp.99-105
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• 2012

Recently, there are many user selection algorithms in multi user multiple-input multiple-output (MU-MIMO) systems. One of well-known user selection methods is Semi orthogonal user selection (SUS). It is an algorithm maximizing channel capacity. However, it is applicable only when user's antenna is one. We propose a generalized user selection algorithm regardless of the number of user's antennas. In the proposed scheme, Base station (Bs) selects the first user who has the highest determinant of channel and generates a user group that correlation with first user's channel is less than allowance of correlation. Then, each determinant of channels made up of first user's channel and a user's channel in the generated group is calculated and BS selects the next user who has the highest determinant of that. BS selects following users by repeating above procedure. In this paper, we get better performance because of selecting users who have the highest determinant of channel as well as allowance of correlation optimally calculated through matrix operations.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2821-2823
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• 2002

In this paper we propose the Multi-FNN (Fuzzy-Neural Networks) for optimal identification modeling of complex system. The proposed Multi-FNNs is based on a concept of FNNs and exploit linear inference being treated as generic inference mechanisms. In the networks learning, backpropagation(BP) algorithm of neural networks is used to updata the parameters of the network in order to control of nonlinear process with complexity and uncertainty of data, proposed model use a HCM(Hard C-Means)clustering algorithm which carry out the input-output dat a preprocessing function and Genetic Algorithm which carry out optimization of model The HCM clustering method is utilized to determine the structure of Multi-FNNs. The parameters of Multi-FNN model such as apexes of membership function, learning rates, and momentum coefficients are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization abilities of the model. NOx emission process data of gas turbine power plant is simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper.

• Journal of The Korean Association of Information Education
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• v.22 no.5
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• pp.605-611
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• 2018

On-Line Lectures are becoming more common due to the MOOK service and the expansion of national policy in Korea. Especially, It is being changed to new remote mixed style from traditional lecture in universities. We propose and implement a remote contents making tool with audio synchronization function based on more with less resources. To implement our proposed algorithm, we design an interactive interface to assign multiple cutting intervals and convert an input video to print a new result. In experimental, we can confirm our algorithm works properly with average performance value 9.3% cpu share ratio and 87mega byte ram usage(CPU 2.60GHz, 820*600 Area).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.7
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• pp.1506-1511
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• 2004

The error control of digital transmission system is a very important subject because of the noise effects, which is very sensitive to transmission performance of the digital communication system It employs a modified Euclid's algorithm to compute the error-location polynomial and error-magnitude polynomial of input data. The circuit size is reduced by selecting the Modified Euclid's Algorithm with one Euclid Cell of mutual operation. And the operation speed of Decoder is improved by using ROM and parallel structure. The proposed Encoder and Decoder are simulated with ModelSim and Active-HDL and synthesized with Synopsys. We can see that this chip is implemented on Xilinx Virtex2 XC2V3000. A share of slice is 28%. nut speed of this paper is 45Mhz.

• The Journal of Information Technology
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• v.5 no.4
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• pp.57-64
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• 2002

The system that is thermal test system for elements has been controlled generally by PID algorithm because of its characteristic. There is not a mathematical model for the system. So the system that is use the PID controller is not properly operated. To solve this problem, we propose a fuzzy algorithm that parameters and rule base is selected by self-searched algorithm for each system. The input fuzzy membership function is adapted based on the set stable range. Output membership function is nearly fixed but some parameter is adjustable. The rule base is changed under basis on the system response. The output value computed through inference and defuzzification is mapped into a value that is proper for the system operation. Through this regulation, it will be possible to prevent the temperature of system to go into the unstable temperature.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.4
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• pp.46-54
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• 2003

In this paper, we propose segmentation algorithm for MR brain images using the histogram of T1-weighted, T2-weighted and PD images. Segmentation algorithm is composed of 3 steps. The first step involves the extraction of cerebrum images by ram a cerebrum mask over three input images. In the second step, peak ranges are determined from the histogram of the cerebrum image. In the final step, cerebrum images are segmented using coarse to fine clustering technique. We compare the segmentation result and processing time according to peak ranges. Also compare with the other segmentation methods. The proposed algorithm achieved better segmentation results than the other methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8B
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• pp.1204-1210
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• 2010

In this paper, in order to reduce the power consumption of LCD TV, we present a two-dimensional dimming algorithm for LED BLU(Backlight Unit) using light spread function and a pragmatic implementation method. In conventional two dimensional dimming algorithms, LED BLU is divided into MxN blocks and proper backlight luminance for each block is computed according to input image and used for dimming control. But, LED light of each block is diffused and affects the neighboring blocks so that luminance of each block becomes larger than that of intent. In the proposed algorithm, dimming control values are reduced by the amount of quantity affected by the neighboring blocks using light spread function, resulting in additional reduction of power consumption.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.3
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• pp.335-341
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• 1998

In this paper, we present a real time implementation of CS-ACELP(Conjugate Structure Algebraic Code Excited Linear Prediction) speech coder. ITU-T has standardized the CS-ACELP algorithm as G.729. Areal-time implementation of CS-ACELP speech coder algorithm is achieved using 16 bit fixed-point DSP chip. To implement in fixed-point DSP Chip, integer simulation of CS-ACELP algorithm is used. Furthermore. input/output function and communication function included in CS-ACELP speech coder is described. We develope CS-ACELP speech coder in DSP evaluation board and evaluate in IMT-2000 Test-bed.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.2
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• pp.37-43
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• 2009

In this study, multi-channel digital hearing aid algorithm for low power system is proposed. First, MDCT(Modified Discrete Cosine Transform) method converts time domain of input speech signal into frequency domain of it. Output signal from MDCT makes a group about each channel, and then each channel signal adjusts a gain using LCF(Loudness Compensation Function) table depending on hearing loss of an auditory person. Finally, compensation signal is composed by TDAC and IMDCT. Its all of process make progress 16-bit fixed-point operation. We use fast-MDCT instead of MDCT for reducing system complexity and previously computed tables instead of log computation for estimating a gain. This algorithm evaluate through computer simulation.