A prediction model is proposed to describe the path loss in propagation environment of indoor microcell. This model includes the lineal corridor for line--of-sight(LOS) and T-shaped corridor for non-line-of-sight(NLOS). In computation of receiving power the ray tracing technique based on image method is utilized and also reflected waves bounced on the walls and ceilings are considered. To check validity of the computed resuls cross checks between the predicted and measured are being made, which shows a close agreement for LOS case whereas somewhat disagreement for NLOS case. UTD technique is incorporated with propagation path determination algorithm in the treatment of NLOS case.

The Nakagami m-distribution is used to model different fading environments and shown to fit experimental resutls more accurately than other distributions. In this paper, the probability of symbol error for M-ary QAM with square signal constellation in frequency-nonselective shlow Nakagami fading and additive white Gaussian noise is derived. When Nakagami fading index is integer, the derived resutls leads to the closed-form of a finite series.

In order to prevent the presence of the residual phase difference at the discriminator output by the existing AFC techniques, we propose a new automatic frequency control(AFC) tracking algorithm for QPSK demodulation at the digital direct broadcasting satellite(DBS) receiver, which we call a rotational decision-directed AFC(RDDAFC). The RDDAFC rotates the decision boundary for the kth received symbol by the frequency deterctor output of the (k-1)th received symbol. Tracking performances of carrier frequency offset by the proposed RDDAFC algorithm are evaluated through computer simulations under the practical DBS channel conditions with a carrier frequency offset of 2.3MHz when S/N equals 2dB. Test results show that the total pull-in time of the RDDAFC is 1.697msec for 10$^{-3}$ SER before forwared error correction at the receiver.

The end-to-end rate-based control mechanism is used for the flow control of the ABR service to allow much more flexibility in ATM switching system. To accommodate the ABR service effciently many algorithms such as EFCI, EPRCA, ERICA, and CAPC2 have been proposed for the switch algorithm. ABR cells and related RM cells are received at the ATM switch fabric transparently without any processing. And then cells received from the traffic source are queued in the ABR buffer of switching system. The ABR buffer usually has some thresholds for easy congestion control signal transmission. Whatever we use, therefore, these can be many ABR traffic control algorithms to implement the ABR transfer capability. The genertion of congestion indicate signal for ABR control algorithms is determined by ABR buffer satus. And ABR buffer status is determined by ABR cells transfer ratio in ATM switch fabrics. In this paper, we presented the functional structures for control of the ABR traffic capability, proposed the readout scheduling, cell slot allocation of output link and the buffer allocation model for effective ABR traffic guranteeing with considering CBR/VBR traffics in ATM switch. Since the proposed readout scheduling scheme can provide more avaliable space to ABR buffer than existing readout scheduling scheme, generation rate of a SEND signal, that is, BCN signal in destination node can be increased for ABR call connection. Therefore, the proposed scheme, in this paper, can be appropriate as algorithm for effective ABR traffic service on output link of ATM switching node.

In this paper, we show an optimal structure of impedance control in high density layouts ina high multilayers PCB. The impedance control in a high multilayers FR-4 PCB is very portant isue because a dielectric layer's thickness is very thin. Especially, odd mode impedance control is more difficult than characteristic impedance control in high multilayers PCB. So, we show an optimal structure of odd mode impedance control in that dielectric thickness is about 0.1mm with limited state and discuss multilayers PCB's for swich circuti pack and backplane in developing algorith scale ATM witching system in next time.

Ultrasonic sensors are widely employed in detecting range to a target by the virtue of their low cost and simplicity. However, the sensor's measurements are corrupted by systematic errors due mainly to the dependency of sound speed upon surrounding conditions and random errors of uncertain origin. In this paper, we present the results of research carried out to reduce these errors for increasing the reliability of an untrasonic sensor system to be used in orbotic or other automated system's range finding. The sensor system designed herein is in a peuliar structure having a reference target and two receivers. Echoes from a small reference target placed at a known distance are used for compensating the variations of sound speed according to the changes of sensing conditions. Unlike existing ones, the technique proposed can compensate the effects of temperature or any other physical parameters without an additional sensor dedicated to the compensation. The measurements by two redundantly employed receivers are fused to reduce random errors in a statistical sense. The correlation of the signals from the receivers sharing a hardware in part is considered in the fusion process. The methodology desicribed in this paepr is conceptually simple, easy to be implemented, and effetive to increase the accuracy of the sensor measurements as experimental results confirm.

In this study, a controller design method is proposed for controlling the discrete-time chaotic systems efficiently. The proposed control method is based on Generalized Predictive Control and uses NARMAX models as controlled models. In order to evaluate the performance of the proposed method, a proposed controller is applied to discrete-time chaotic systems, and then the control performance and initial sensitivity of the proposed controller are compared with those of the conventional model-based controler through computer simulations. Through simulations results, it is shown that the control performance of the proposed controller is superior to that of the conventional model-based controller and shown that the peorposed controller is less sensitive to initial values of discrete-time chaotic systems in comparison with the conventional model-based controller.

The design and implementation of a drive wheel position, orientation, and velocity feedback control algorithm for a differential-drive mobile robot is described here. A new concept, the most significant error, is introduced as the control design objective. Drive wheel position, orientation, and velocity feedback control directly minimize the most siginificant error by coordinating the motion of the two drive wheels. The drive wheel position, orientation, and velocity feedback control algorithm is analyzed and experiments are conducted to evaluate its performance. The experimental results are shown that drive wheel position, orientation and velocity feedback control algorithm yields substantially smaller position and orientation errors than those of conventional methods.

This paepr is concerned with the design of linear parameter varying filter that ensures H$^{2}$/$H^{\infty}$ performance for a class of linear parameter varying(LPV) plants. The state space matrices of plant are assumed to be dependent affinely on a vector of time varying parameter, and each parameter is assumed to be measured in real time. Using the linear matrix inequalities(LMIs), we can solve the synthesis problem and the solution of LMIs is carried out off-line. The designed filter is parameter varying and automatically scheduled along parameter trajectories. Because the solution of LMIs is carried out off-line, computation time of filter gain is reduced. The validity of the proposed algorithm is verifed through computer simulation..

This research focuses onan efficient control method of temperature for multiple points using only one processor. For a yarn production system, the surface temperature control of heaters are very important for quality control. Therefore, we designed a temperature controller for a draw and twist machine and applied Fuzzy-PWM algorithm to the controller. If we use a processor for the temperature control of multiple points with the conventional ON/OFF control, the control performance of the system becomes poor. To overcome these problems, we developed a new Fuzzy-PWM algorithm for the adjustment of power rate to the heaters in the conventional ON/OFF control. It is shown that this algorithm has the same effects as the PID algorithm for the temperature control of each point. The proposed algorithm is robust against the production condition and environment such as the reference temperature and the thickness of yarn, since the power rate to the heater is adjusted by Fuzzy Rules derived from the values of the reference termperatureand the thickness of yarn. To obtain optimal Fuzzy rulees, the control simulations are perfodrmed through the modelling of the heater and simulation of Fuzzy rules. This algorithm is applied for the multiple pont temperature controller and showed satisfactory performance.

A Hausdorff distance (HD) is one of commonly used measures for object matching. It calculates the distance between two point sets of edges in two-dimensional binary images without establishing correspondences. This paper proposes three object matching algorithm using robust HD measures based on M-estimation, least trimmed square (LTS), and .alpha.-trimmed mean methods, which are more efficient than the conventional HD measures. By computer simulation with synthetic and real images, the matching performance of the conventional HD smeasures and proposed' robust ones is compared.

In this paepr, a new image segmentation method reducing efficiently contour information causing bottleneck problem at segmentatio-based very low bit rate codingis proposed, while preserving objective and subjective quality. It consists of 4-level hierarchical image segmentation based on mathematical morphology and 1-leve region merging structure using contast of two adjacent regions. For two adjacent region pairs at the fourth level included in each region of the thid level, contrast is calculated. Among the pairs of two adjacent regions with less value than threshold, two adjacent regions having the minimum contrast are merged first. After region merging, texture of the merged region is updated. The procedure is performed recursively for all the adjacent region pairs at the fourth level included in each region of the third level. Compared with the previous method, the objective and subjective image qualities are similar. But it reduces 46.65% texture information on the average by decreasing total region number to be tansmitted. Specially, it shows reduction of the 23.95% contour information of the average. Thus, it can improve efficiently the bottleneck problem at segementation-based very low bit rate coding.

This paper presents a method that automatically recognizes dimension sets from the mechanical drawings, and that classifies 6 types dimension sets according to functional purpose. In the proposed method, the object and closed-loop symbols are separated from the character-free drawings. Then object lines and interpretation lines are vectorized. And, after recognizing dimension sets(consistings of arrowhead, shape line, tail lines, extension lines, text-string, and feature control frame), we classify recognized dimension sets as horizontal, vertical, angular, diametral, radial, and leader dimension sets. Finally the proposed method converts classified dimension sets into AutoCAD data by using AutoLisp language. By using the methods of geometric modeling, the proposed method readily recognized and classifies dimension sets from complex drawings. Experimetnal results are presented, which are obtained by applying the proposed method to drawings drawn in compliance with the KS drafting standard.

This paper describes the algorithm which can estimate road following direction and deetect obstacle using a monocular vision system. This algorithm can estimate the course of vehicle using the vanishing point properties and detect obstacle by statistical method. The proposed algorithm is composed of four steps, which are lane prediction, lane extraction, road following parameter estimation and obstacle detection. It is designed for high processing speed and high accuracy. The former is achieved by a small area named sub-windown in lane existence area, the later is realized by using connected edge points of lane. We would like to present that the new mehod can detect obstacle using the simple statistical method. The paracticalities of the processing speed, the accuracy of the algorithm and proposing obstacle detection method, have been justified through the experiment applied VTR image of the real road to the algorithm.

The ultrasonic images are corrupted by the granular pattern noise - a speckle noise. The speckle exist in the type of coherent imaging systems, and the speckle is the signal independent and multiplicative noise. In this paepr, we derive two filters using the gradient and symmetry. One is a noise suppression filter which removes noise while preserves the edges. It is named the ASRF-GS (Adaptive Speckle Removal Filer - Gradient and Symmetry). And the other is a edge detection filter which obtains the thin edge map, called the EDUGS(Edge Detection Using Gradient and Symmetry). The performance of the proposed noise suppression filter is evaluated by the IMPV(SNR improvement) and the Speckle Index(SI), and the perforamnce of the edge detection is evaluated by the edge detection error rate. According to the evaluated method, The SI reduced about 0.035, The IMPV improved about 1.265(dB), and the edge detection error rate is about 17.5%.

Ths signal processing technqiue of FET type electrolyte sensors using the back propagation neural network was studied to reduce the interference effects of the different electrolytes. The FET-type electrolyte sensors, pH-ISFET, K-ISFET, and Ca-ISFET, were prepared to measure the pH, K, and Ca electrolytes. Neural network consisted of three layers was learned with 8 patterns and 9 patterns. The sensor output obtained with arbitrary concentrations was processed by the learned neural network. The errors obtained from calibration curve for pH, K, and Ca were .+-.0.039 pH, .+-.2.508 mmol/l, and .+-.1.807 mmol/l, respectively, without considering the interference effects. The errors of the network output for pH, K, and Ca were reduced to .+-.0.005 pH, .+-.0.436 mmol/l, and .+-.0.381 mmol/l in case of 9 patterns, respectively. the signal processing using the neural network can reduce the errors ofthe electrolyte sensor outputs caused by the interference effect, thereby providing effectiveness in the improvement of the sensor selectivity.

Recently, the three phase AC to DC boost converter has become one of the most widely used power converters as DC power source in the industry applications. In this paepr, a three phase PWM AC toDC boost converter that operates with unity power factor and sinusodial input currents is presented. The current control of the converter is based onthe predicted current control strategy with fixed switching frequency and the input current tracks the reference cuent within one sampling time interval. Therefore, by using this control strategy low ripples in the output voltage, low harmonics in the input current and fast dynamic responses are achieved with a small capacitance in the DC link.