• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.3
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• pp.79-89
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• 1998

The Error Back-Propagation(EBP) algorithm is widely applied to train a multi-layer perceptron, which is a neural network model frequently used to solve complex problems such as pattern recognition, adaptive control, and global optimization. However, the EBP is basically a gradient descent method, which may get stuck in a local minimum, leading to failure in finding the globally optimal solution. Moreover, a multi-layer perceptron suffers from locking a systematic determination of the network structure appropriate for a given problem. It is usually the case to determine the number of hidden nodes by trial and error. In this paper, we propose a new algorithm to efficiently train a multi-layer perceptron. OUr algorithm uses stochastic perturbation in the weight space to effectively escape from local minima in multi-layer perceptron learning. Stochastic perturbation probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the probabilistically re-initializes weights associated with hidden nodes to escape a local minimum if the EGP learning gets stuck to it. Addition of new hidden nodes also can be viewed asa special case of stochastic perturbation. Using stochastic perturbation we can solve the local minima problem and the network structure design in a unified way. The results of our experiments with several benchmark test problems including theparity problem, the two-spirals problem, andthe credit-screening data show that our algorithm is very efficient.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.5
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• pp.490-495
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• 1999

In this paper. a learning method VoD-EBP for neural networks is proposed, which learn patterns by error back propagation. Based on Voronoi diagram, the method initializes the weights of the neural networks systematically, wh~ch results in faster learning speed and alleviated local optimum problem. The method also shows better the reliability of the design of neural network because proper number of hidden nodes are determined from the analysis of Voronoi diagram. For testing the performance, this paper shows the results of solving the XOR problem and the parity problem. The results were showed faster learning speed than ordinary error back propagation algorithm. In solving the problem, local optimum problems have not been observed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.3A
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• pp.325-333
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• 2000

The proposed RPSS(Reference Picture Segment Selection) mode is the RPS mode in picture segment of the ISD mode. The RPS mode has the weakness that it has to change the whole reference picture even if transmission error occurs only in the small part of picture. If the RPS mode is applied only to an error-occurred part and a conventional coding scheme is applied to an error-free part, the higher coding efficiency can be obtained. Simulation results show that there is the optimal number of segment which provides that best performance with given environment such as the BER(Bit Error Rate) of wireless channels, the characteristics of imput sequence, what kind of RPSS mode is used, etc. To apply the channel-adoptive RPSS mode later, the scheme which can change the number of segment without INTRA refresh and spatial error propagation is proposed in this paper.

• Proceedings of the Korea Concrete Institute Conference
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• 2003.05a
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• pp.175-180
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• 2003

Ultrasonic pulse velocity method is applied many times for measuring surface crack depth of concrete in case of diagnosis of concrete structures. By the way, this method has an error accompanying measured surface crack depth of concrete because there are many uncertainty factors. So, it is necessary to study for an error of this method affected by these uncertainty factors. Two error factors(uncertainty factors) are tested and analyzed in this study. One is for an error according to measuring the propagation time of ultrasonic wave and the arrangement distance of transducers. Another is for an error according to positioning the transducer as a distance to surface crack from the transducer.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.263-266
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• 2009

When video packets are transmitted over error-prone networks, the leaky prediction can be used to mitigate the effect of error propagation. The leaky factor provides trade-off between coding efficiency and error resilience in the leaky prediction. In this paper, we propose an improved leaky prediction method where the leaky factor is adaptively determined for each frame by minimizing the estimated end-to-end distortion at the encoder. Experimental results show that the proposed method with the adaptive leaky factor shows the better performance of the error robustness as compared with the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.3
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• pp.331-337
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• 2016

In this paper, we analyze performances of in-band full-duplex communication system and self-interference (SI) suppression methods in environment where there exists the SI signal. The SI has to be removed to achieve required error rate performance of the system in order - propagation domain, analog domain and digital domain. In propagation domain, the SI signal is attenuated by separating transmitted and received beams physically. In analog and digital domain, after reconstruction of the SI signal using channel estimates and transmit signal, the SI signal can be cancelled from the desired signal. In this paper, assuming that the SI signal can be sufficiently reduced in propagation domain, we demonstrate that the in-band full-duplex communication system can achieve the target error rate by suppressing the SI signal in order - analog and digital domain, based on channel estimates that can be obtained by the method of Least squares.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.211-217
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the teaming control field was teaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.

• 전자공학회논문지 IE
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• v.48 no.2
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• pp.6-11
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• 2011

This paper describes the design of new method of propagation delay measurement in micro and nanostructures during characterization of ASIC standard library cell. Providing more accuracy timing information about library cell (NOR, AND, XOR, etc.) to the design team we can improve a quality of timing analysis inside of ASIC design flow process. Also, this information could be very useful for semiconductor foundry team to make correction in technology process. By comparison of the propagation delay in the CMOS element and result of analog SPICE simulation, we can make assumptions about accuracy and quality of the transistor's parameters. Physical implementation of phase error accumulation method(PHEAM) can be easy integrated at the same chip as close as possible to the device under test(DUT). It was implemented as digital IP core for semiconductor manufacturing process($0.11{\mu}m$, GL130SB). Specialized method helps to observe the propagation time delay in one element of the standard-cell library with up-to picoseconds accuracy and less. Thus, the special useful solutions for VLSI schematic-to-parameters extraction (STPE), basic cell layout verification, design simulation and verification are announced.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1059-1065
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• 2014

Wind turbine system can obtain the maximum wind energy using torque control under the rated wind speed, and wind turbine power is controlled as the rated power using pitch control over the rated wind speed. In this paper, we present a method for wind turbine pitch controller using neural networks. The purpose of the pitch control is to control generator speed and power in the above rated wind speed. To improve the neural network pitch controller, the difference between a rated and current speed of generator has been used for another input of neural networks as well as wind speed. Error back-propagation algorithm is used for training the neural network pitch controller and simulation and Matlab/Simulink is used for verifying that this system is controlled well.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.2
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• pp.40-47
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work the authors presented an iterative precision of linear decentralized learning control based on p-integrated teaming method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the loaming control field was learning in robots doing repetitive tasks such as on a]1 assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Error wave propagation method will show up in the numerical simulation for five-bar linkage as a vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link at each time step in repetition domain. Those can be helped to apply to the vertical multiple dynamic systems for precision quality assurance in the industrial robots and medical equipments.