Nowadays, one of the serious problems in KEPCO system is the larger fault current than the SCC(Short Circuit Capacity) of circuit breaker. There are many alternatives to reduce the increased fault current such as isolations of bus ties, enhancement of SCC of circuit breaker, applications of HVDC-BTB(Back to Back) and FCL(fault current limiter). However, these alternatives have some drawbacks in viewpoints of system stability and cost. As the superconductivity technology has been developed, the HTS-FCL(High Temperature Superconductor-Fault Current Limiter) can be one of the attractive alternatives to solve the fault current problem. Under this background, this paper presents the EMTDC model for resistive type HTS-FCL considering the nonlinear characteristic of final resistance value when quenching Phenomena occur.

This paper presents a generalized predictive control method based on a fuzzy neural network(FNN) model, which uses the on-line multi-step prediction, fur the intelligent control of chaotic nonlinear systems whose mathematical models are unknown. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of FNN are determined adaptively during the operation of the system. In order to design a generalized predictive controller effectively, this paper describes computing procedure for each of the two important parameters. Also, we introduce a projection matrix to determine the control input, which deceases the control performance function very rapidly. Finally, in order to evaluate the performance of our controller, the proposed method is applied to the Doffing and Henon systems, which are two representative continuous-time and discrete-time chaotic nonlinear systems, res reactively.

In this paper, the contrast enhancement method of thermal image is proposed and it is the plateau equalization algorithm using local histogram for the real time display of infrared imagery. Through hardware implementing, its practicality and adequacy are proved. Examinations are executed to verify the effect of contrast enhancement by bright control and contrast control automatic to the plateau value in the manual mode, and that verified the effect of contrast enhancement in the automatic mode and the practicality in the real system. According to the experiment results, the proposed "the application of local histogram and plateau equalization algorithm for contrast enhancement of real time thermal image"in this dissertation is the verified method for the thermal imaging contrast enhancement.

The DCT algorithm needs an efficient hardware architecture to compute inner product. The conventional design method, like ROM-based DA(Distributed Arithmetic), has large hardware complexity. Because of this reason, a CSHM(Computation Sharing Multiplication) was proposed for implementing inner product by Park. However, the Park's CSHM has inefficient hardware architecture in the precomputer and select units. Therefore it degrades the performance of the multiplier. In this paper, we presents the optimization design method for inner product using CSHM algorithm and applied it to implementation of 1-D DCT processor. The experimental results show that the proposed multiplier is more efficient than Park's when hardware architectures and logic synthesis results were compared. The designed 1-D DCT processor by using proposed design method is more high performance than typical methods.

The digital electronic switching system has some problems, when this system processes OAM(Operation, Administration And Maintenance) messages about the fault, the traffic, the account, and the performance, etc., at the present. One of these problems is that each the module processing these messages in the digital electronic switching system can not process OAM messages out of another digital electronic switching system. Each the module processing these OAM messages, that is, has been programmed in order to process only the OAM message out of the digital electronic switching system mounting itself, not to process the message out of the digital electronic switching system based on another platform. Therefore, we studied on methods that could process OAM messages out of all digital electronic switching systems and, first of all, developed the MGS(Message Gathering System) to be able to accept and process the fault message of OAM messages out of all digital electronic switching systems in real time.

This paper proposes a new method on the EMG AR(autoregressive) modeling in pattern recognition for various head motions. The proper electrode placement in applying AR or cepstral coefficients for EMG signature discrimination is investigated. EMG signals are measured for different 10 motions with two electrode arrangements simultaneously. Electrode pairs are located separately on dominant muscles(S-type arrangement), because the bandwidth of signals obtained from S-type placement is wider than that from C-type(closely in the region between muscles). From the result of EMG pattern recognition test, the proposed mIAR(modified integrated mean autoregressive model) technique improves the recognitions rate around 17-21％ compared with other the AR and cepstral methods.

The low-power design of the A/D converter is indispensable to achieve the compact bio-signal measuring device with long battery duration. In this paper, new decimation filter structure is proposed for the low-power design of the Sigma-Delta A/D converter in the bio-instruments. The proposed filter is based on the non-recursive structure of the CIC (Cascaded Integrator Comb) decimation filter in the Sigma-Delta A/D converter. By combining the CSD (Canonic Signed Digit) structure with common sub-expression sharing technique, the proposed decimation filter structure can significantly reduce the number of adders for implementation. For the fixed decimation factor of 16, the 15％ of power consumption saving is achieved in the proposed structure in comparison with that of the conventional polyphase CIC filter.

The modified Wiener filtering method is proposed for effective noise suppression in edge region of images corrupted by additive white gaussian noise. Although the pixels classified as a edge region in the conventional Wiener filter have lots of noise components, the conventional Wiener filter cannot remove noise effectively due to the preserving of edges. To reduce noise well in edge region, we modify filter coefficients of the conventional Wiener filter. The modified filter coefficients increase in noise suppression effect in edge region, while they preserve edges for strong edge region. From simulation (256${\times}$256 size, 256 graylevel images) filtered images by the proposed method show much improved subjective image quality with higher peak signal-to-noise ratio compared to those by the conventional Wiener filtering.

In this paper, human motor behaving model based sensory motor coordination(SMC) algorithm is implemented on robotic grasping task. Compare to conventional SMC models which connect sensor to motor directly, the proposed method used biologically inspired human behaving system in conjunction with SMC algorithm for fast grasping force control of robot arm. To characterize various grasping objects, pressure sensors on hand gripper were used. Measured sensory data are simultaneously transferred to perceptual mechanism(PM) and long term memory(LTM), and then the sensory information is forwarded to the fastest channel among several information-processing flows in human motor system. In this model, two motor learning routes are proposed. One of the route uses PM and the other uses short term memory(STM) and LTM structure. Through motor learning procedure, successful information is transferred from STM to LTM. Also, LTM data are used for next moor plan as reference information. STM is designed to single layered perception neural network to generate fast motor plan and receive required data which comes from LTM. Experimental results showed that proposed method can control of the grasping force adaptable to various shapes and types of greasing objects, and also it showed quicker grasping-behavior lumining time compare to simple feedback system.