In this paper, we studies the on-line recognition of handwritten character using WLD(weighted levenshtein distance) algorithm with parallelism. The Hangeul can be separated for unit of phonemes and the alphanumeric can be separated for unit of characters. And, we studies the parallelism and the concurrency of the WLD algorithm for realization of special-purpose processor. By the simulation result for 10, 000 characters in practical sentences, the recognition rate of strokes in obtained 96.57$\%$ and the separation rate for phonemes and characteristics is obtained 95.4$\%$.

In this paper, we propose a new formant locus overlapping method which can effectively enhance a naturalness of synthetic speech produced by ddemisyllable based Korean text-to-speech system. At first, Korean demisyllables are divided into several number of segments which have linear formant transition characteristics. Then, database, which is composed of start point and length of each formant segments, is provided. When we synthesize speech with these demisyllable database, we concatenate each formant locus by using a proposed overlapping method which can closely simulate haman articulation mechanism. We have implemented a Korean text-to-speech system by using this method and proved that the formant loci of synthetic speech are similar to those of the natural speech. Finally, we could illustrate that the resulting spectrograms of proposed method are more similar to natural speech than those of conventional method.

This paper suggests a measure constraint locus for characterization of the performance of a subtask for a redundant robot. The measure constraint locus are the loci of points satisfying the necessary constraint for optimality of measure in the joint configuration space. To uniquely obtain an inverse kinematic solution, one must consider both measure constraint locus and self-motion manifolds which are set of homogeneous solutions. Using measure constraint locus for maniqulability measure, the invertible workspace without singularities and the topological property of the configuration space for linding equilibrium configurations are analyzed. We discuss some limitations based on the topological arguments of measure constraint locus, of the inverse kinematic algorithm for a cyclic task. And the inverse kinematic algorithm using global maxima on self-motion manifolds is proposed and its property is studied.

다수의 출력변수를 가지고 있는 실시스템에서, 출력변수의 측정치가 어떠한 사정(하드웨어상 혹은 제어대상의 특성 등)에 의하여 동시에 전부 검출되어지지 않고, 측정방식이나 성분이 유의한 것끼리 몇개씩 서로 조금씩 틀린 시각에 측정되어 차례로 디지틀 계산기에 입력되어지는 경우가 있다. 다시 말하면, P개의 검출량이 조금씩 틀린 시각 $kT_{o}+t_{1},kT}o}+t_{2}.{\cdot}{\cdot}{\cdot},kT_{o}+t_{r}(0{\le}t_{1}{<}t_{2}{<}{\cdot}{\cdot}{\cdot}{<}t_{r}{<}T_{0})$에 각각 $P_{1},P_{2},{\cdot}{\cdot}{\cdot},P_{r}(P=P_{1}+P_{2}+{\cdot}{\cdot}{\cdot}+P_{r})$개씩 측정되어 얻어지게 된다/ 본 논문에서 말하는 다중 시리얼 샘플링이라고 하는 것은 이와같은 데이터의 취득방식을 의미하고 있다. 종래의 관측기이론에서는 P개의 검출량을 가진 제어대상의 상태추정에는 P개이 데이터를 동시에 필요로 하고 있다. 따라서 종래의 관측기이론을 그대로 상기와 같은 대상에 적용하게 되면, P개의 측정치가 전부 얻어지는 시간 $T_o$마다 상태의 추정치를 갱신하는 관측기가 얻어진다. 그러므로, 이와같은 관측기를 사용하게 되면 임의의 시각에 한조의 출력변수가 검출되더라도 그 정보를 직접 이용하지 못하고 나머지의 출력변수가 전부 검출될 때까지 기다리지 않으면 안되게 되므로, 하드웨어사의 기능을 최대한 이용하지 못하고 있는 것이 아닌가 생각된다. 본 논문에서는 상기와 같은 시스템에 있어서, 한조의 출력변수가 검출될 때마다 관측기의 내부상태를 갱신해서 새로운 상태추정치를 얻을 수 있는 $'$다중시리얼 샘플링형 관측기$'$를 제안하고 그의 구성가능성을 증명한다. 또한, 다중시리얼 샘플링형 관측기의 출력으로 폐루프를 구성하였을 경우, 전체 제어계의 안정성에 관한 문제를 검토하고, 시뮬레이션에 의하여 본 논문에서 제안된 관측기의 유효성을 확인한다.유효성을 확인한다.

A learing method for the recognition of printed Chinese character by using the input driven multi-layer perceptron model was proposed and the circuit representing the learning result was designed. In learning the extracted features from Chinese characters are used as inputs and the synapse's weight is integer value. So it is possible to implement the learning result with CMOS circuit.

The congestion control methods of an integrated heterogeneous traffic multiplexer are studied. The real-time traffics have preemptive priority over nonreal-time traffics in capturing the common output link. Also real-time traffics are transmitted with bandwidth reduction when the nonreal-time traffics are over the buffer threshold. The proposed model formulated the system as a continous time Markov process and is analysed using matrix equation. Time delay and average number of used channel are applied for performance parameters. In this study, a new control method with the sizable buffer threshold is introduced and the optimal congestion control can be obtained.

Utilizing dual basis, normal basis, and subfield representation, three different finite field multipliers are presented in this paper. First, we propose an extended dual basis multiplier based on Berlekamp's bit-serial multiplication algorithm. Second, a detailed explanation and design of the Massey-Omura multiplier based on a normal basis representation is described. Third, the multiplication algorithm over GF(($2^{n}$) utilizing subfield is proposed. Especially, three different multipliers are designed over the finite field GF(($2^{4}$) and the complexity of each multiplier is compared with that of others. As a result of comparison, we recognize that the extendd dual basis multiplier requires the smallest number of gates, whereas the subfield multiplier, due to its regularity, simplicity, and modularlity, is easier to implement than the others with respect to higher($m{\ge}8$) order and m/2 subfield order.

A mulitpath MIN(Multistage Interconnection Network), CSMP(Chained Shuffle Multi-Path) network, is proposed, having fault-tolerance and dynamic reroutability. The number of stages and the number of links between adjacent stagges are the same as in single path MINs, so the overall hardware complexity is considerably reduced in comparison with other multipath MINs. The CSMP networks feature links between switches belonging to the same state, forming loops of switches. The network can tolerate multiple faults, up to (N/4)*(log$_2$N-1), having occured in any stages including the first and the last ones(N:NO. of input). To analyze reliability, terminal reliability (TR) and mean time to failure( MTTE) age given for the networks, and the TR figures are compared to those of other static and dynamic rerouting multipath MINs. Also the MTTE figures are compared. The performance of the proposed network with respect to its bandwidth (BW) and probability of acceptance(PA) is analyzed and is compared to that of other more complex multipath MINs. The cost efficiency analysis of reliability and performance shows that the network is more cost-effective than other previously proposed fault-tolerant multipath MINs.

In this paper, we propose a new process for ultrasonic B-mode image considering the sound field effects of a concave circuit focused transducer, and aim to remove the speckle pattern which cause the blurring on boundary in ultrasonic B-mode image. We discuss in detail the conception of speckle pattern generation, and the frequency compounding method which is applied to the process for getting a speckle reduced B-mode image. Through the computer simulation, we define the meaning of speckle region, and show the results of reduced speckle pattern. It is discovered in the results that the frequency compounding method is very effective for boundary detection and that the application of the method is limited by various conditions.

A combined model of probabilistic and MLP(multi layer perceptron) model is proposed for the pattern classification of EMG( electromyogram) signals. The MLP model has a problem of not guaranteeing the global minima of error and different quality of approximations to Bayesian probabilities. The probabilistic model is, however, closely related to the estimation error of model parameters and the fidelity of assumptions. A proper combination of these will reduce the effects of the problems and be robust to input variations. Proposed model is able to get the MAP(maximum a posteriori probability) in the probabilistic model by estimating a priori probability distribution using the MLP model adaptively. This method minimize the error probability of the probabilistic model as long as the realization of the MLP model is optimal, and this is a good combination of the probabilistic model and the MLP model for the usage of MLP model reliability. Simulation results show the benefit of the proposed model compared to use the Mlp and the probabilistic model seperately and the average calculation time fro classification is about 50ms in the case of combined motion using an IBM PC 25 MHz 386model.

The automatic target detection which automatically identifies the location of the target with its input image is one of the significant subjects of image processing field. Then, there are some problems that should be solved to detect the target automatically from the input image. First of all, the ambiguity of the boundary between targets or between a target and background should be solved and the target should be searched adaptively. In other words, the target should be identified by the relative brightness to the background, not by the absolute brightness. In this paper, to solve these problems, a new algorithm which can identify the target automatically is proposed. This algorithm uses the set of fuzzy for solving the ambiguity between the boundaries, and using the weight according to the brightness of data in the input image, the target is identified adaptively by the relative brightness to the background. Applying this algorithm to real images, it is experimentally proved that it is can be effectively applied to the automatic target detection.