• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.572-577
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• 2009

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. To prune the redundant speech segments in a large speech segment DB, we can utilize a decision-tree based triphone clustering algorithm widely used in speech recognition area. But, the conventional methods have problems in representing the acoustic transitional characteristics of the phones and in applying context questions with hierarchic priority. In this paper, we propose a new clustering algorithm to downsize the speech DB. Firstly, three 13th order MFCC vectors from first, medial, and final frame of a phone are combined into a 39 dimensional vector to represent the transitional characteristics of a phone. And then the hierarchically grouped three question sets are used to construct the triphone trees. For the performance test, we used DTW algorithm to calculate the acoustic similarity between the target triphone and the triphone from the tree search result. Experimental results show that the proposed method can reduce the size of speech DB by 23% and select better phones with higher acoustic similarity. Therefore the proposed method can be applied to make a small sized TTS.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1550-1556
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• 1997

In this paper, we apply the evolutionary algorithm to the combinatorial optimization problem. Evolutionary algorithm useful for the optimization of the large space problem. This paper propose a method for the reuse of wastes of light water in atomic reactor system. These wastes contain several reusable elements, and they should be carefully selected and blended to satisfy requirements as an input material to the heavy water atomic reactor system. This problem belongs to an NP-hard like the 0/1 knapsack problem. Two evolutionary strategies are used as approximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method which perform the feasible test and solution evaluation by using the vectored knowledge in problem domain. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

• Journal of IKEEE
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• v.1 no.1 s.1
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• pp.19-30
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• 1997

In this paper we design the optimal satellite-tracking antenna $H{\infty}$ control system using genetic algorithms. To do this, we give gain and dynamics parameters to the weighting functions and apply genetic algorithms with reference model to the optimal determination of weighting functions and design parameter ${\gamma}$ that are given by Glover-Doyle algorithm which can design $H{\infty}$ controller in the state space. These weighting functions and design parameter ${\gamma}$ are optimized simultaneously in the search domain guaranteeing the robust stability of closed-loop system. The effectiveness of this satellite-tracking antenna $H{\infty}$ control system is verified by computer simulation.

• The KIPS Transactions:PartC
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• v.11C no.1
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• pp.75-80
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• 2004

An iterative soft-decision decoding algorithm of block codes is proposed. With careful examinations of the first hard-decision decoding result, the candidate codewords are efficiently searched for. An approach to reducing decoding complexity and lowering error probability is to select a small number of candidate codewords. With high probability, we include the codewords which are at the short distance from the received signal. The decoder then computes the distance to each of the candidate codewords and selects the codeword which is the closest. We can search for the candidate codewords which make the error patterns contain the bits with small reliability values. Also, we can reduce the cases that we select the same candidate codeword already searched for. Computer simulation results are presented for (23,12) Golay code. They show that decoding complexity is considerably reduced and the block error probability is lowered.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.218-223
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• 2011

Various research studies are underway to explore music classification by genre. Because sound professionals define the criterion of music to categorize differently each other, those classification is not easy to come up clear result. When a new genre is appeared, there is onerousness to renew the criterion of music to categorize. Therefore, music is classified by emotional adjectives, not genre. We classified music by light and shade in precedent study. In this paper, we propose the music classification system that is based on emotional adjectives to suitable search for atmosphere, and the classification criteria is three kinds; light and shade in precedent study, intense and placid, and grandeur and trivial. Variance Considered Machines that is an improved algorithm for Support Vector Machine was used as classification algorithm, and it represented 85% classification accuracy with the result that we tried to classify 525 songs.

• Journal of Korean Society for Quality Management
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• v.46 no.1
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• pp.169-188
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• 2018

Purpose: The purpose of this study is to analyze low-temperature starting performance of the light attacker and to search and improve the aircraft system including battery and Battery Charge and Control Unit(BCCU). Methods: In order to improve the starting up performance of the light attacker at low-temp, various deficiency cause were derived and analyzed using Fault Tree Analysis method. As a result, it was confirmed there were drawbacks in the charging and discharging mechanism of the battery. The inactivation of the battery's electrolyte at low-temp and the premature termination of the battery charge were the main cause. After long error and trial, we improved these problems by improving performance of battery and optimizing the charging algorithm of BCCU. Results: It was confirmed that the problems of starting up failures were solved through the combined performance test of the battery and BCCU, the ground test using the aircraft system and the operation test conducted by Korea Airforce operating unit for 3 months in winter. Conclusion: This study showed that the improvement of quality reliability was achieved and thus the start-up performance issue of the light attacker has been resolved at low temperature. And it is expected that the design methodologies of temperature-affected electrical system of aircraft will contribute to the development of the aircraft industry in the future.

• Journal of Korea Water Resources Association
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• v.38 no.3 s.152
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• pp.199-212
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• 2005

The study on the plan for rehabilitation project of domestic water distribution system - especially using Heuristic Algorithm as Genetic Algorithm which is expected to provide a more optimal solution effectively - has not been done sufficiently. The purpose of this study is the development of the optimal decision making system for the rehabilitation of the water distribution system considering economic and hydraulic influences using ReHS which is recent study of OR technique. Five different models with different objective functions are developed and tested to virtual pipe network according to various conditions considered in this study. These models provide more options for the rehabilitation of pipe network systems compared to previously suggested models in the literature.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2A
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• pp.112-120
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• 2010

In this paper, we propose semi-ML adaptive parallel QRDM (APQRDM) and iterative QRDM (AIQRDM) algorithms based on set grouping. Using the set grouping, the tree-search stage of QRDM algorithm is divided into partial detection phases (PDP). Therefore, when the treesearch stage of QRDM is divided into 4 PDPs, the APQRDM latency is one fourth of that of the QRDM, and the hardware requirements of AIQRDM is approximately one fourth of that of QRDM. Moreover, simulation results show that in $4{\times}4$ system and at Eb/N0 of 12 dB, APQRDM decreases the average computational complexity to approximately 43% of that of the conventional QRDM. Also, at Eb/N0 of 0dB, AIQRDM reduces the computational complexity to about 54% and the average number of metric comparisons to approximately 10% of those required by the conventional QRDM and AQRDM.

• The Journal of the Acoustical Society of Korea
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• v.37 no.2
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• pp.118-128
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• 2018

In this paper, we have studied how to search an underwater object by learning the image generated by the side scan sonar in the convolution neural network. In the method of human side analysis of the side scan image or the image, the convolution neural network algorithm can enhance the efficiency of the analysis. The image data of the side scan sonar used in the experiment is the public data of NSWC (Naval Surface Warfare Center) and consists of four kinds of synthetic underwater objects. The convolutional neural network algorithm is based on Faster R-CNN (Region based Convolutional Neural Networks) learning based on region of interest and the details of the neural network are self-organized to fit the data we have. The results of the study were compared with a precision-recall curve, and we investigated the applicability of underwater object detection in convolution neural networks by examining the effect of change of region of interest assigned to sonar image data on detection performance.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.4
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• pp.35-41
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• 2002

To solve the large scale optimization problem approximately, various approaches have been introduced. They are mainly based on recent research advancement of simulations for evolutions, flocking, annealing, and interactions among organisms on artificial environments. The typical ones are simulated annealing(SA), artificial neural network(ANN), genetic algorithms(GA), tabu search(TS), etc. Recently the particle swarm optimization(PSO) has been introduced. The PSO simulates the process of birds flocking or fish schooling for food, as with the information of each agent Is share by other agents. The PSO technique has been applied to various optimization problems of which variables are continuous. However, there are seldom trials for visualization of searching process. This paper proposes a new visualization tool for searching process particle swarm optimization(PSO) algorithm. The proposed tool is effective for understanding the searching process of PSO method and educational for students.