• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2613-2625
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• 1997

Theoretically, a multi-layered feedforward network has been known to be able to approximate a continuous function to an arbitrary degree of accuracy. However, these networks fail to approximate discontinuous functions when they are trained by well-known training algorithms. This paper presents a training algorithm which doesn't work consists of one or more modules, which are trained in a sequential order within subspaces of the input space, and is trained very rapidely once all modules are trained and merged. The experimantal results of applying this method indicates the proposed training algorithm is superior to traditional ones such as baskpagation.

• The Journal of Information Technology
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• v.1 no.1
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• pp.65-84
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• 1998

The MBR (Memory Based Reasoning) is a supervised learning method that utilizes the distances among the input and trained patterns in its classification, and is also called a distance based learning algorithm. The MBR is based on the k-NN classifier, in which teaming is performed by simply storing training patterns in the memory without any further processing. This paper proposes a new learning algorithm which is more efficient than the traditional k-NN classifier and has incremental learning capability, Furthermore, our proposed algorithm is insensitive to noisy patterns, and guarantees more efficient memory usage.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.3
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• pp.125-131
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• 2012

This paper is on a stereo acoustic echo canceller with the blind signal separation. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals in the update signal of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 3dB higher ERLE in the case of using the BSS algorithm than the case of not using the BSS algorithm. But this echo canceller didn't get good performances in the case of inputting the white noises as stereo signals.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.1985-1996
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• 1998

A parallelising algorithm for partitioning and mapping methods of matrix/vector multiplication into linear processor array/VLW simulator is presented in this paper. First we discuss the mapping methods for input matrix or vector into the arbitrarily size of processor arrays. Then, we show partitioning the algorithmss of the large size of computational problem into the size of the processor array. We execute the algorithm on VLIW simuhator and show to effectiviness of algorithm. The result which we achived better parallelising performance on our VLIW simulator dsign than on linear processor array.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.508-509
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• 2007

For the safty driving of an automobile which is become individual requisites, a new Neural Network algorithm which recognized the load vehicles in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.1
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• pp.228-246
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• 2011

A 3D model based approach for a face representation and recognition algorithm has been investigated as a robust solution for pose and illumination variation. Since a generative 3D face model consists of a large number of vertices, a 3D model based face recognition system is generally inefficient in computation time and complexity. In this paper, we propose a novel 3D face representation algorithm based on a pixel to vertex map (PVM) to optimize the number of vertices. We explore shape and texture coefficient vectors of the 3D model by fitting it to an input face using inverse compositional image alignment (ICIA) to evaluate face recognition performance. Experimental results show that the proposed face representation and recognition algorithm is efficient in computation time while maintaining reasonable accuracy.

• Annual Conference of KIPS
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• 2013.11a
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• pp.768-770
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• 2013

We propose a symmetric key based cryptography algorithm to encode and decode the text data with limited length using 3-dimensional magic square matrix. To encode the plain text message, input text will be translated into an index of the number stored in the key matrix. Then, Caesar's shift with pre-defined constant value is fabricated to finalize an encryption algorithm. In decode process, Caesar's shift is applied first, and the generated key matrix is used with 2D magic squares to replace the index numbers in ciphertext to restore an original text.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.04a
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• pp.409-416
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• 2004

An active modal-fuzzy control method using hydraulic actuators is presented for seismic response reduction. In the proposed control system, a new fuzzy controller designed in the modal space produces the desired active control force. This type controller has all advantages of the fuzzy control algorithm and modal approach. Since it is very difficult to select input variables used in fuzzy controller among an amount of state variables in the active fuzzy control system the presented algorithm adopts the modal control algorithm which is able to consider more easily information of all state variables in civil structures that are usually dominated by first few modes. In other words, all information of the whole structure can be considered in the control algorithm evaluated to reduce seismic responses and it can be efficient for especially civil structures. In addition, the presented algorithm is expected to magnify utility and performance caused by efficiency that the fuzzy algorithm can handle complex model more easily. An active modal-fuzzy control scheme is applied together with a Kalman filter and a low-pass filter to be applicable to real civil structures. A Kalman filter is considered to estimate modal states and a low-pass filter was used to eliminate spillover problem. The results of the numerical simulations far a wide amplitude range o f loading conditions and for historic earthquakes having various frequency components show that the proposed active modal-fuzzy control system can be beneficial in reducing seismic responses of civil structures.

• Journal of Korean Library and Information Science Society
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• v.46 no.1
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• pp.1-23
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• 2015

The purpose of this paper is to development an algorithm for FRBR implementation(functional requirements for bibliographic records), analyzing KORMARC bibliographic records by work types. For this purpose, it was utilized analyzing home and foreign case studies including OCLC and LC's algorithm. Analyzing the experimental data from the Korean National Library's bibliographic records, it was extracted from identifying elements by FRBR's four bibliographic entities. To cluster a related works by work-set, the algorithm was designed to construct the authorized access points as a combination of an author name and a title from the record. I suggested that it should be wholly improved a quality of existing bibliographic records and level of data input to development a FRBR algorithm in Korean libraries.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2310-2316
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• 1997

This paper presents a comparative performance analysis of the stochastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criterion with other widely-used competing adaptive algorithms. Under the assumption that the signals involved are zero-mean, wide-sense stationary and Gaussian, approximate expressions that characterize the steady-state mean-squared estimation error of the algorithm is dervied. The validity of our derivation is then confirement by computer simulations. The convergence speed is compared under the condition that the LMAT and other competing algorithms converge to the same value for the mean-squared estimation error in the stead-state, and superior convergence property of the LMAT algorithm is observed. In particular, it is shown that the LMAT algorithm converges faster than other algorithms even through the eignevalue spread ratio of the input signal and measurement noise power change.