There are many challenging problems in mobile robot navigation. As an example, a mobile robot may wander around in local minimum and may wiggle when it moves through a narrow corridor. In addition, the real time obstacle avoidance and the posture control of mobile robot are also very improtant problems. To address these problems, a navigation algorithm which is composed o freal time obstacle avoidance algorithm and a global path planner (GPP) that genrates the shortest path is presented. In this paper, the global path planner reduce the calculation time by reducing the dta to be handled. Also it can make a real time obstacle avoidance by using the fuzzy logic inference. So the presented algorithm provide a stable navigastion for the mobile robot when it fall into the unstable navigation.

In this paper, the performance of the IeEE 802.4 token-passing is analyzed under the assumption that all nodes have finite buffers and finite THT (token tolding time). The loads generated at nodes are assumed to be asymmetric. The priority mechanism is not considered. This paper derives an approximate matrix equation of the queue length distributin in terms of the number of nodes, frame arrival rate and mean service time of a frame in steady state. Based on the matrix equation, the mean token rotation time, the mean waiting time and the blocking probability are derived analytically. the analytic results are compared with simulation results in order to show that the deviations are small.

An intelligent integrated control system is designed for the active steering and the left/right traction force distribution control of electric vehicles, where input-output linearization is employed. Also, a fuzzy-rule-based cornering force estimator is suggested to avoid using an uncertain highly nonlinear expression, and a neural network compensator is additively utilized for the estimator to correctly find cornering forece. With these techniques, the proposed control system is shown by simulation results to be robust against drastic change of the external environments such as road conditions.

In this paper, we describe the algorithm which controls an unknown nonlinear system with multilayer neural network. The multilayer neural netowrk can be used to approximate any continuous function to any desired degree of accuracy. With the former fact, we approximate unknown nonlinear function on the nonlinear system by using of multilayer neural netowrk. The weights on the hidden layer of multilayer neural network are updated by gradient method. The weight-update rule on the output layer is derived to satisfy lyapunov stability. Also, we obtain secondary controller form deriving step. The global control system consists of controller using feedback linearization method and secondary controller is order to satisfy layapunov stability. The proposed control algorithm is verified through computer simulation.

An unified compliant control algorithm to regulate the force by dual arms is proposed, where tow arms are treated as one arm in a kinematic viewpoint. The force error calculated form the information of two force/torque sensors attached to the end of each arm is transferred to minimum actuator coordinates, and then is distributed to total system actuator coordinates. The position adjustment at the total actuator coordinates is computed based on the effective computed based on the effective compliance matrix with respect to total actuator coordinates, which is obtained by coordinate transformation between the task coordinates and the total actuator coordinates. An experiment is carried out for dual arms with asymmetric kinematic structure to control an interaction force between manipulators and the environment. The performances of the proposed control algorithm are experimentally compared to those of dual arms employing master/slave scheme. The proposed compliant control algorithm not only ouperforms other algorithms, but also can be treated as an unified approach n the sense that it can be applied to arbitrary dual arm systems with general kinematic structures.

The current network environment is composed of heterogeneous H/W and S/W resources. Integrating CSCW applications in such heterogeneous environments is highly complex. This paper describes the design and implementation of ASS (application sharing server) which supprot sharing of a single application between different operating systems. The ASS supports cooperative work among user group using its own window system (X-windwo or MS-windwos). We adopted improved managing heavy-weight data. ASS also provides development environment for vaious groupware application.

To retrieve complex data such as images in multimedia information, we need the content-based retrieval methods based on the visual properties rather than keywords. In this paper, a contrent-based image retrieval system is desinged and implemented to retrieve images using the features of images such as colors, lines and intensity vetor features when a visual query inputs. The contents for image retrievals are the color features extracted from the color component of 16 blocks of the image, th eline features extracted form 4 lines in the image and the shape features extracted from the intensity vectors of the 16 blocks. We can either use a whole image or a sketch image for query. As the experimental results demonstrate the precision 91% the recall 33% and the average rank 3.1 the retrieval performance is found to be high. The experimental results indicate that the retrieval using the weighted features have led to substantial improvement in the percision and performance of system.

To increase the functionality of the memories, previous studies have deifned faults models and proposed functional testing algorithms with low complexity. Although conventional testing depended strongly on functional (voltage) testing method, it couldn't detect short and open defects caused by gate oxide short and spot defect which can afect memory reliability. Therefore, IDDQ (quiescent power supply current) testing is required to detect defects and thus can obtain high reliability. In this paper, we consider resistive shorts on gate-source, gate-drain, and drain-source as well as opens in mOS FET and observe behavior of the memory by analyzing voltage at storge nodes of the memory and IDDQ resulting from PSPICE simulation. Finally, using this behavioral analysis, we propose a linear testing algorithm of complexity O(N) which can be applicable to both functional testing and IDDQ testing simultaneously to obtain high functionality and reliability.

A sinusoidal tuned VCO based on linear OTA's has been designed for instrumentation and measurement applications. It consists of a noniverting amplifier, a hard limiter, and a current controlable LC-tuned circuit which is realized vy two linear OTA's and two grounded capacitors. A prototype circuit has been built with discrete components. The experimental results show that the proposed VCO has a linearity error of less than 6.5 percent and a temperature coefficient of less than 200ppm/$^{\circ}C$ over a bias current range form 5$\mu$A to 100 $\mu$A(or an oscillation frequency range form 775.5 Hz to 20.371 kHz). A total harmonic distortion of 0.6 percent was measured for a peak-to-peak amplitude of 5V.

Modulation and demodualtion circuits of chaos frequency shift keying have been implemented using chua's circuits. The modulatin circuit, which is designed ot perform the frequency-doubling by coupled synchronization wihtout changing the intrinsic characteristics of its two chaos signals generated, modulates the digital input signals. The demodulation circuit detects the digital input signals form carrier by drive synchronization. these circuits, which are simplest until now and have no restriction to their digital input amplitudes, perform the aimed functions.

Estimation and removal procedures for baseline drift have been developed using linear, cubic spline, and bilineared transformed high pass filter. Linear and cubic spline interpolation with the PQ and TP segmens, which are considered to be isoelectric, as fiducial points ahve been estimated respectively. For a quantitative validation of the estimation procedure, 4 ECGs with arfificial baseline drift were constructed and analyzed by mean square error calculations and amplitude histograms. Also real ECGs were analyzed in a test set of the CSE data set 3 and set 4. Baseline drift detecton rule were designed and new method for the decision of fiducial point were constructed to avoid distorting as the case of premature ventricular or atrial contraction. From these comparison, proposed cubic spline method with PQ and TP segment (CS_PQ & TP) emerged as the most efficient method.

The average distortio of the vector quantizer is calcualted using a probability function F of the input source for a given codebook. But, since the input source is unknown in geneal, using the sample vectors that is realized from a random vector having probability function F, a time-average opeation is employed so as to obtain an approximation of the average distortion. In this case the size of the smple set should be large so that the sample vectors represent true F reliably. The theoretical inspection about the approximation, however, is not perfomed rigorously. Thus one might use the time-average distortion without any verification of the approximation. In this paper, the convergence characteristics of the time-average distortions are theoretically investigated when the size of sample vectors or the size of codebook gets large. It has been revealed that if codebook size is large enough, then small sample set is enough to obtain the average distortion by approximatio of the calculated tiem-averaged distortion. Experimental results on synthetic data, which are supporting the analysis, are also provided and discussed.

In this paper, we propose a new termination rule for the iterative restoration of degraded images, by which the number of iterations can be dramatically reduced. This rule uses a parameter, called noise suppression factor (NSF), to appropriately teminate the iteration process, reduces a lot the computational load, and avoids the amplification of noise for the better quality. We also propose a method using the morphological filters, when applied to the resulting image, that will significantly reduce the ringing effect which would otherwise exist in the boundary of the image. Simulation with the blurred lena image with gaussian noise showns that the proposed termination rule combined with the morphological filtering gives the restored image with much improved quality.

The 3-dimensional measurement using stereo vision system must achieve a camera calibration. So far, the 3-dimensional calibration technique that uses two-dimensional grid papar and a non-linear least square method has been developed and tested. But, this method is inefficient because it has many calculation procedure and a non-linear analysis. Therefore, this paper proposed the projective geometric method which produced the calibration parameter by vanishing point. The vanishing point is producted by a cross ratio and a parallel line pairs. The results of the computer simulation show utility of the proposed method.

In this paper, w epropose a new mehtod to represent the shape and to recognize the object. The shape description and the matching is implemented by using the distance transform on the morphological skeleton. The employed distance transform is the chamfer (3,4) distance transform, because the chamfer distance transform (CDT) has an approximate value to the euclidean distance. The 2-D object can be represented by means of the distribution of the distance transform on the morphological skeleton, the number of skeletons, the sum of the CDT, and the other features are employed as the mtching parameters. The matching method has the invariant features (rotation, translation, and scaling), and then the method is used effectively for recognizing the differently-posed objects and/or marks of the different shape and size.

For shape invariant recognitin of korean characters iwth noise, an optical wavelet SDF filter is proposed To preserve the features of a reference image and inimize effects of a random noise in the inpt image wavelet transformed images with different dialation parameters are used. And to adapt to divese variations in the combinatorial form, eCP-SDF filter synthesis algorithm is used. The proposed optical wavelet SDF filter is the type of the matched filter so that it can use the structure of 4f optical correlation system. The computer simulation results show that the proposed filter is useful in the noisy input.

The test and evaluation is a integal part of the radar development process and it consists of two parts, field test and in-house test using a standard simulated signal. To take the in-house test, the test environment is needed to generate the critical signal that is used to determine the system design parameters and consists of general urpose measurement equipments, specialized boards and operating softwares. This paper presents the in-house test environment configuration and its function for radar system. Because this test environment genrates the simulated radar signal which has arbitrary flight path and target condition, the developed test environment makes easily to evaluate the function for radar system. The program ability of test parameters makes it possible to apply a test for 2D and 3D radar system.

Recently, it was reported that gaussian distribution and difference of two gaussians (DOG) to have band pass characteristics can be generated by simple iterative processes of the diffusion networks. In this paper, we propose method of improved implementation of a diffusion filter which can reduce total runing time, and operate by simple algorithm in contrast to the latest diffusion filter. We rebuild the diffusion network to a difference network which can generate DOG independently. Different filter characteristics are obtained just by each diffusion process and difference process. Quantitative analysis shows that the center frequency and the selectivity of each filter channel can be varied independently. Also, it would requires smaller amount of hardwares than conventioanl method to build a filter bank.

In this paper, we propose the parallel, self-organizing, hierarchical neural netowrks as a handwritten digit recognition system. This system can absorb the various shape variations of handwritten digits by using the different methods of extracting the features in each stage neural network (SNN) of the PSHNN, and can reduce training time by using the single layer neural network as the SNN, and can obtain high rate of correct recognition by using the certainty area in all the output nodes individually. experiments have been performed with NIST database. In which we use 21, 315 digits (10, 625 digits for training and 10,663 digits for testing). The results show that the correct rate is 97.48% the error rate is 1.72% and the reject rate is 0.78%.

In this paper, we propose a new method which estimates the initial position of a PM synchronous motor (PMSM) using an incremental ecoder. in cremental encoders are widely used in detecting rotor position since they are inexpensive. At starting procedure, however, the incremental encoders cannot give the information of the absolute rotor position. Hence, additional absolue encoder, which has $60^{\circ}C$ resolutio electrically, and signal lines called U, V, W, have been used in practical systems for starting injection of a high frequency test current. It does not require any additional information such as U, V, W signals for starting procedure and allows for cheap and simple implementation. Experimental results show that the proposed method can estimate the initial rotor positon with higher accuracy than the conventional method using U, V, W signals.