In this paper, a new method of phoneme segmentation of handwritten Korean characters using the local graph pattern is proposed. At first, thinning was performed before extracting features. End-point, inflexion-point, branch-point and cross-point were extracted as features. Using these features and the angular relations between these features, local graph pattern was made. When local graph pattern is made, the of strokes is investigated on contacting point. From this process, pattern is simplified as contacting pattern of the basic form and the contacting form we must take into account can be restricted within fixed region, 4therefore phoneme segmentation not influenced by characters form and any other contact in a single character is performed as matching this local graph pattern with base patterns searched ahead. This experiments with 540 characters have been conducted. From the result of this experiment, it is shown that phoneme segmentation is independent of characters form and other contact in a single character to obtain a correct segmentation rate of 95%, manages it efficiently to reduce the time spent in lock operation when the lock.

In the new database applications such as office information systems, CAD/CAM, and AI, it is required to support not only fixed Is-A and Part-Of relationships but also various user-defined dynamic relationships including complicate constraints. However, existing object-oriented systems have many weaknesses in managing those complex relationships. This paper presents the Object-Oriented Relationship data Model (OORM) which is designed to provide facilities for modeling complex relationships into object oriented databases using abstraction concept. In the model, various integrity and consistency constraints related to the relationships can be also represented. And this paper presents a query language, ORSQL(Object Relationship SQL). ORSQL is a nonprocedural query language having similiar syntax to the standard SQL and supporting OORM's operations.

Network systems are of fundamental importance in programmable device in industrial automation, as they essential in order to active group management of integration and coordination. In this papers,MMS implemented on the basis ISO specification for industrial environment. In the MMS-MAP, MMS is situated in the application layer and on the datalink layer. This implemented software was operated with network interface unit which was designed in group objects and service primitives for group management network model system. This function of designed module showed possibility of operation through group state diagram transition in the Mini-MAP environment.

This paper proposes a shortest path allocation algorithm over the processors on the hypercube system based on the message passing techniques with the optimized module allocation. On multiprocessor systems, how to divide one task into multiple tasks efficiently is an important issue due to the hardness of the life cycle estimation of each process. To solve the life cycle discrepancies, the appropriate task assignment to each processor and the flexible communications among the processors are indispensible. With the concurrent program execution on hypercube systems, each process communicaties to others with the method of message passing. And, each processor has its own memory. The proposed algorithm generates a callable tree out of the module, assigns the weight factors, constructs the allocation graph, finds the shortest path allocation tree, and maps them with hypercube.

In this paper, we proposed a new optical method for the efficient recognition of Korean characters. There are six filters in the proposed method which employed the concepts of amplitude-modulated phase-only filter(AMPOF) and spatial frequency modulation(SFM). Here, amplitude modulation is used to achieve improved correlation discrimination and SFM is to reduce the number of filters. We also used a simplified synthetic discriminant function(SDF) for distortion invariance of input image. In order to recognize the partial rotation invariant Korean characters, the proposed distortion invariant minimum average correlation energy (MACE) filter is synthesized SFM, partial rotation invariant filter (PRIF), AMPOF and MACE for partial rotation invariance in the frequency domain. The advantage of the proposed filters is to supress the sidelobes of cross correlation peak away from the autocorrelation peak and to produce sharp correlation peaks. We performed simulation and optical experiment for some of Korea characters using the proposed method. The results show that the proposed method has more improved discriminant ability and reduced processing time than the conventional methods.

In this paper, a fuzzy logic controll(FLC) is designed for the pointing loop of the spinstabilized platform. For the fuzzy inference, a fuzzy accelerator board using the Togai InfraLogic software and digital fuzzy processor(DFP110FC) is designed, and a validation of an algorithm for fuzzy logic control is also presented. Through the simulation and the experiment, it can be seen that the designed FLC shows better performance than a conventional controller using the same loop gain.

The Fourier series are employed to approximate the input/output(I/O) characteristics of a dynamic system and, based on the approximation, a new learing control algorithm is proposed in order to find iteratively the control input for tracking a desired trajectory. The use of the Fourier approximation of I/O renders at least a couple of useful consequences: the frequency characteristics of the system can be used in the controller design and the reconstruction of the system states is not required. The convergence condition of the proposed algorithm is provided and the existence and uniqueness of the desired control input is discussed. The effectiveness of the proposed algorithm is illustrated by computer simulation for a robot trajectory tracking. It is shown that, by adding feedback term in learning control algorithm, robustness and convergence speed can be improved.

In this thesis, general method using autoregressive model in the functional separation of the myoelectric signal of human arm movements are suggested. Covariance method and sequential least squares algorithm were used to determine the model parameters and the order of signal model to describe six arm movement patterns` the forearm flexion and extension, the wrist pronation and supination, rotation-in and rotation out. The confidence interval to classify the functions of arm movement was defined by the mean and standard deviation of total squares error. With the error signals of autoregressive(AR) model, the result showed that the highest success, rate was abtained in the case of 4th order, and success rate was decreased with increase of order. This technique might be applied to biomedical-and rehabilitation-engi-neering.

In this paper, we propose the test pattern generation algorithm of the embedded faulty MUX for the prevention of misdiagnosis of digital systems. When the system is partitioned with a large number of functional blocks, if the faults are exsisted in a embedded MUX then it can not diagnose the wanted observation of functional block. The proposed test pattern generstion algorithm can apply the MUXs that designd 2-level and multi-level both. Fault coverage becomes 100% and so it is no necessary of the additional fault simulation and the proposed algorithm that have the regulary and easily generated 2d test patterns. And we confirmed that the reduction of test cost becomes 85%, compared with the conventional segmentation testing scheme.

In this paper, we propose an adaptive classifier based on uncertainty of features for 3D planar object recognition. First, we investigate the uncertainty of depth information and the feature values of 3D planar object by numerical method. And, we observed that the statistical behavior of feature is dependent on the position and orientation of objects. After that, the approximation of the statistical behavior is executed. Subsequently, the recognition procedure is executed by the adaptive classifier. By computer simulation, we confirmed that the proposed classifier is useful for 3D planar object recognition.

The motion compensated coding (MCC) technique, which exploits the temporal redundancies in the moving images with the motion estimation technique,is one of the most popular techniques currently used. Recently, a variable block size(VBS) motion estimation scheme has been utilized to improve the performance of the motion compensted coding. This scheme allows large blocks to the used when smaller blocks provide little gain, saving rates for areas containing more complex motion. Hence, a new VBS motion estimation scheme with a hierarchical structure is proposed in this paper, in order to combine the motion vector coding technique efficiently. Topmost level motion vector, which is obtained by the gain/cost motion estimation technique with selective motion prediction method, is always transmitted. Thus, the hierarchical VBS motion estimation scheme can efficiently exploit the redundancies among neighboring motion vectors, providing an efficient motion vector encoding scheme. Also, a restricted search with respect to the topmost level motion vector enables more flexible and efficient motion estimation for the remaining lower level blocks. Computer simulations on the high resolution image sequence show that, the VBS motion estimation scheme provides a performance improvement of 0.6~0.7 dB, in terms of PSNR, compared to the fixed block size motion estimation scheme.

This paper proposes an on-line Recognition scheme of cursive Korean characters based on the DP matching and fuzzy concept. The proposed algorithm, invariant to rotation and size, reduces greatly the computational requirement of dynamic programming by matching phonemes rather than character patterns, where the angle difference and the ration of lengths between input and reference patterns are adopted as matching features. The correct matching of poorly written cursive characters becomes possible by introducing the fuzzy concept in representing the features of phonemes and the ralative position between adjacent phonemes. Computer simulation results are observed to show the effectiveness of the proposed algorithm.

In this paper, A progressive coding of mean difference pyramid by Hadamard transform of the difference between two successive pyramid levels has been studied. A block adaptive bit allocation method based on ac energy of each sub-block has been proposed, which efficiently reduces the final distortion in the progressive transmission of image parameters. In our scheme, the dc energy equals the sum of the quantization errors of the Hadamard transform coefficients at previous level. Therefore proposed allocation method includes the estimation of dc energy at each pyramid level. Computer simulation results show some improvements in terms of MSE and picture quality over the conventional fixed allocation scheme.

It is known that the performance of a fuzzy controller is related with fuzzification method, inference rules, defuzzification method, and linguistic variables. Among these, generally, the linguistic variables and control rules are transfered to control engineers from an expert or experts of the controlled system and other parts are designed by control engineers. However, there may be some missed infirmations or uncertainties in the transfered data. The purpose of the paper is to propose an algorithm to tune the membership functions of initially given fuzzy sets To do so, a simple shape of the membership fuction is assumed for the fuzzy sets, and the relations between the shapes of the fuzzy sets and the performance of the control system is derived. According to the relations, the shape of the membership functions are modified during operation of the whole system. The proposed algorithm will be applied to two emample plants, type 1 and type 0 systems.