• Journal of the Korean Society of Industry Convergence
• /
• v.22 no.5
• /
• pp.511-517
• /
• 2019

Two type pistons which had different configuration were made to find out the effects on combustion and flame propagation. Flame propagation speed was obtained by use of the cylinder head gasket ionization probe. Ionization Probe voltage output and flame propagation speed were increased according to the air fuel mixture ratio increase. Exhaust direction flame propagation speed was fastest in combustion chamber and next was front direction, rear direction and intake direction cause of tumbling motion in cylinder. In case of remove the valve pocket in piston, average flame propagation speed changed slowly and spark timing was advanced. Also emission was decreased.

• Phonetics and Speech Sciences
• /
• v.7 no.4
• /
• pp.17-25
• /
• 2015

For blind source separation of convolutive mixtures, FDICA(Frequency Domain Independent Component Analysis) algorithms are generally used. Since FDICA algorithm such as Sawada FDICA, IVA(Independent Vector Analysis) works on the frequency bin basis with a natural gradient descent method, it takes much time to converge. In this paper, we propose a new method to improve convergence speed in FDICA algorithm. The proposed method reduces the number of iteration drastically in the process of natural gradient descent method by applying a weighted inner product constraint of unmixing matrix. Experimental results have shown that the proposed method achieved large improvement of convergence speed without degrading the separation performance of the baseline algorithms.

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.1011-1014
• /
• 1999

In this paper, a new algorithm has been presented that helps to preserve diversity as well as to enhance the convergence speed of the evolutionary programming. This algorithm is based on the cell partitioning of search region for preserving the diversity. Until now, the greater part of researches is not concerned about preserving the diversity of individuals in a population but improving convergence speed. Although these evolutions are started from multi-point search at the early phase, but at the end those search points are swarming about a one-point, the strong candidate. These evolutions vary from the original idea in some points such as multi-point search. In most case we want to find the only one point of the best solution not several points in the vicinity of that. That is why the cell partitioning of search region has been used. By restricting the search area of each individual, the diversity of individual in solution space is preserved and the convergence speed is enhanced. The efficiency of the proposed algorithm has been verified through benchmark test functions.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.30B no.8
• /
• pp.54-63
• /
• 1993

This paper proposes a method for improving the performances of the neural network for optimization by an optimal estimation of initial states. The optimal initial state that leads to the global minimum is estimated by using the stochastic approximation. And then the update rule of Hopfield model, which is the high speed deterministic algorithm using the steepest descent rule, is applied to speed up the optimization. The proposed method has been applied to the tavelling salesman problems and an optimal task partition problems to evaluate the performances. The simulation results show that the convergence speed of the proposed method is higher than conventinal Hopfield model. Abe's method and Boltzmann machine with random initial neuron output setting, and the convergence rate to the global minimum is guaranteed with probability of 1. The proposed method gives better result as the problem size increases where it is more difficult for the randomized initial setting to give a good convergence.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2003.10a
• /
• pp.31-34
• /
• 2003

In recent, the rapid convergence of telecommunication and broadcasting has been considered as one of the hot issues in the IT industry. This convergence will provide telecom operators with both opportunities and threatens. This is because that telecom operators can enter the broadcasting industry, whereas broadcasters will also have a chance to provide telecom services. This work aims to discuss the business strategy for telecom operators to provide a TV VOD service, one of the convergence services between telecommunication and broadcasting, through the high-speed internet which is so much served in Korea. It seems that this service will achieve two business goals, namely "to minimise an additional investment" and "to find out a new benefit source", by fully utilising a current high-speed internet infrastructure. Finally, this paper mainly contains the market overview of in telecom and broadcasting service, the definition of TV VOD service and the necessity for this service, a market forecasting and the provision strategy of major telecom operators, and key success factors and a benefit model.

• Proceedings of the KIEE Conference
• /
• 1998.07b
• /
• pp.644-646
• /
• 1998

The main drawback of filtered-X LMS(FXLMS) algorithm for the ANC of broadband noises is its low convergence speed when the filtered reference signals are strongly correlated, producing a large eigenvalue spread in correlation matrix. This correlation can be caused either by autocorrelation of the signals of the reference sensors, or by coupling between the error path which introduces intercorrelation in the filtered reference signals. In this paper, we introduce a transform domain FXLMS(TD-FXLMS) algorithm that has a high convergence speed by orthogonal transform's decorrelation properties.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.3
• /
• pp.333-343
• /
• 2006

In this paper, the baseline-length information is directly modeled as a measurement for the Wald test, which speeds up the resolution convergence of the integer ambiguity of GPS carrier phase measurements. The convergent speed improvement is demonstrated using numerical simulation and real experiments. It is also shown that the integer ambiguities can be resolved using only four actual satellite measurements with very reasonable convergence speed, if the baseline-length information is used just like one additional observable satellite measurement. Finally, it is shown that the improvement of convergence speed of the Wald test is due to the increase of the probability ratio with the use of the baseline-length constraint.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.34S no.8
• /
• pp.74-83
• /
• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.4
• /
• pp.110-118
• /
• 1997

Multi-layer neural networks with error back-propagation algorithm have a great potential for identifying nonlinear systems with unknown characteristics. However, because they have a demerit that the speed of convergence is too slow, various methods for improving the training characteristics of backpropagition networks have been proposed. In this paper, a fuzzy division method is proposed to improve the convergence speed, which can find out an effective fuzzy division by the tuning of membership function and independently train each neural network after dividing the network model into several parts. In the simulations, the proposed method showed that the optimal fuzzy partitions could be found from the arbitray initial ones and that the convergence speed was faster than the traditional method without the fuzzy division.

• Journal of the Institute of Convergence Signal Processing
• /
• v.9 no.4
• /
• pp.295-303
• /
• 2008

In general, transform domain adaptive filters show faster convergence speed than the time domain adaptive filters, but the amount of calculation increases dramatically as the filter order increases. This problem can be solved by making use of the subband structure in transform domain adaptive filters. In this paper, to increase the convergence speed on the generalized subband decomposition FIR adaptive filters, a structure of the adaptive filter with subfilter of dyadic sparsity factor in wavelet transform domain is designed. And, in this adaptive filter, the equivalent input in transform domain is derived and, by using the input, the convergence properties for the LMS algorithm is analyzed and evaluated. By using this sub band adaptive filter, the inverse system modeling and the periodic noise canceller were designed, and, by computer simulation, the convergence speeds of the systems on LMS algorithm were compared with that of the subband adaptive filter using DFT(discrete Fourier transform).