In this paper, we propose a Neural Call Admission Control (CAC) method using a Sparse Distributed Memory(SDM). CAC is a key technology of TM network traffic control. It should be adaptable to the rapid and various changes of the ATM network environment. conventional approach to the ATM CAC requires network analysis in all cases. So, the optimal implementation is said to be very difficult. Therefore, neural approach have recently been employed. However, it does not mett the adaptability requirements. because it requires additional learning data tables and learning phase during CAC operation. We have proposed a neural network CAC method based on SDM that is more actural than conventioal approach to apply it to CAC. We compared it with previous neural network CAC method. It provides CAC with good adaptability to manage changes. Experimenatal results show that it has rapid adaptability and stability without additional learning table or learning phase.

For constructionof the next generation satellite B-ISDN/ATM networks considering integration with terrestrial information infrastructure networks, various high speed and wideband satellites with be launched and they will make used of frequency reue techniques for efficient management of limited frequency resource. Therefore, CCI(Co-Channel Interference) inherent in frequency reuse will be a dominant factor in performance degradation of satellite networks. This paper alanyzes the ATM cell transmission performance degradation caused by CCI. The satellite link, including up-link and down-link thermal noise, CCI, and nonlinear satellite transponder, is modeled and interleaving technique is used for compensating the ATM cell transmission performance degradation caused by burst error of satellite link. First, each satellite link subsystem is analyzed in detail and then end-to-end ATM cell transmission performance is evaluated with BER and CLR. Specifically, ATMcell transmission performance degradation caused by CCI is evaluated in detail.

This paper is concerned with the implementation of the equalization technique in a DCS 1800 system employing the soft-decision output Viterbi algorithm (SOVA), which makes the hardware complexity comparable to the hard decision MLSE and gives reliable performance. Also, the channel estimation technique with enhances the perfdormance of the soft-decision output equalizer is proposed, and the Viterbi decoder which operates effectively with the soft-decision output of the qualizer is implemented using the Very High Speed ICs Hardware Description Language (VHDL). From the simulation results, it is shown that the implemented Viterbi decoder operates effectively and the SOVA outperforms the hard-decision MLSE in terms of the frame erasure rate (FER) and bit error rate (BER).

This ppaer suggests a congestion control scheme for CL(ConnectionLess) overlay network using the feedback loops getween CL werver, between CL servers, and the header translation table of CL server. The CL overlay network for CBDS(Connectionless Broadband Data Service) defined by ITU0T(International Telecommunication Union-Telecommunication) consists of CL servers which route frames and links which connect between CL user and CL server or between CL servers. In this CL overlay network, two kinds of congestions, link congestion and CL server congestion, may occur. We suggest a scheme that can solve the congestion using ABR(Available Bit Rate) feedback control loop, the traffic control mechanism. This scheme is the link-by-link method suing the ABR feedback control loops between CL user and CL server or between CL servers, and the header translation table of CL server. As CL servers are always endpoints of ABR connections, the congestion staturs of the CL server can be informed to the traffic sources using RM(Resource Management) cell of the ABR feedback loops. Also CL server knows the trafffic sources making congestion by inspecting the source address field of CLNAP-PDUs(ConnectionLess Network Access Protocol - Protocol Data Units). Therefore this scheme can be implemeted easily using only both ABR feedback control loop of ATM layer and the congestion state table using the header translation table of CL server because it does not require separate feedback links for congestion control of CL servers.

In the FDMA and TDMA Cellular Systems, call blocking rise when frewquence slots andtime slots are used to ther users. Otherwise, in the CDMA cellular systems, call locking arises when interference level is above 10dB according to call of other users. System capacity is defined to be Erlang capacity that is the number of users when CDMA blocking probability is 1% or 2%. Users number corresponded channel number of AMPS and TDMA cellular systems. In this paper, we proposed new reuse-fraction using square of interference poser and obtained Erlang capacity for reverse link of CDMA cellular system with bit rate $R_{b}$, 9.6kbps and 14.4kbps. As a results, Erlange capacity of CDMA system have more 20.7 and 5.5 times than AMPS and TDMA system and have more form 1 to 4 Erlang thatn Viterbi and Padovani obtaned.d.

Multi-dimensional DC-free trellis codes based on two-dimensional constellation which can be omplemented more easily than conventional codes are proposed and their performances are analyzed in this paper. 2N-dimensional constellation of the proposed codes is constructed by concatenating N 2-dimensional constellation. Thus, for the proposed codes, information bits can be assigned easily to each signal point of the 2-dimensional consteellation and DC-free characteristic can be simply obtained by the symmetric structure of the constellation. In addition, since Viterbi decoder can calculate multi-dimensional Euchlidean distance between signals by simple sum of each 2-dimensional Euclidean distanc, decoding complexity can be reduced. The performance analysis shows that the proposed codes have almost same spectral characteristic and error performance as compared with conventional codes. However, the complexity is shown to be reduced further due to the construction method of contellation and the simple decoding algorithm of the proposed codes.

In this paper, a cell scheduling algorithm is proposed to satisfy the service requirements of CBR, VBR traffics. Particularly, inthe proposed algorithm an ABR traffic which is not included in the conventional cell schedulaing algorithm is treated as one kind of traffic types. The algorithm of RT-VBR and NRT-VBR traffic such that the service requrements of RT-VBR and NRT-VBR traffic are satisfied. The proposed algorithm dynamically schedules cells in a real time by considerin the current traffic conditions. The simulation of the proposed algorithms such as WRR or DWRR in terms of the mean delay time and the maximum queue length.

We consider connection-oriented wireless cellular networks such as the second generation wireless cellular networks and wirelss ATM networks. In these networks, a separate forward signaling channel is provided for the transmission of paging and channel allocation packets. When a call destined to a user is requested, all the base stations in the user's current location area broadcast the corresponding paging packet across forward signaling channels. By slot mode operation and paging group allocation for fusers in a location area, we can reduce relative power consumption level at battery-operated terminals. However, a sthe number of paging groups is increased for lowering relative power consumption level, a paging packet experiences higher delay to access the forward signaling channel. For the pre-negotiated quality-of-service level, paging packet delay level must be limited. In this paper, we consider static and dynamic multiplexing schemes for paging packets, and develop an analytical method for calculating paging packet delay and relative power consumption levels. Using this analytial method, we investigate the effect of network parameters on the paging packet delay and relative power consumption levels.

In this paper, a fuzzy tuning method of a control gain in the discrete-time repetitive controller is proposed for precise tracking control of a system whose reference signal is repetitive. The control gain is modified by fuzzy rules which use the magnitude and the variation ofthe maximum output error in the previous repetitive period. The proposed method is applied to a direct drive 2-axis SCARA-type robot and, it is illustratedby computer simulations and real-time experimentation that better performance can be obtained that the fixed gain-based repetitive controller.

This paper deals with an output feedback H control problem for linear time ivariant systems with state delay. The proposed output feedback controller is represented by the lower linear fractional transformation of alinear time invariant system and a delay operator. Sufficient conditions for the existence of the output feedback controller are given in the form of linear matrix inequalities which are less conservative than those for the existence of a rational output feedback controler. We also present a numerical example to demonstrate the efficacy of the proposed method.of the proposed method.

In Integrated Tube Components(ITC) process in themanufacturing of color display tube, we describe the necessity of the convergence measurement method using photo sensors. Compared with methods using 1D or 2D cameras, its characteristics is to use of moving image patterns and fixed sensors. This measurement method is formulated as the measurement problem of the phase difference in phase changing periodic signals. The convergence measurement system using photo sensors, for the good performance, must have a small standard deviation for the repetitive measurement in the same condition and a fast measurement time for thecovergence change. By above two conditions, we proposed the real time measurement algorithm of the pahse difference using fundametal and harmonic in phase changing periodic signals. And, the proposed algorithm is applied to the convergence measurement system.

In this paper, we propose a method of cooperative control based on immune system in distributed autonomous robotic system(DARS). Immune system is living body's self-protection and self-maintenance system. Thus these features can be applied to decision making of optimal swarm behavior in dynamically changing environment.For the purpose of applying immune system to DARS, a robot is regarded as a B lymphocyte(B cell), each environmental condition as an antigen, and a behavior strategy as an antibody respectively. The executing process of proposed method is as follows. When the environmental codintion changes, a robot select an appropriate beharior stategy. And its behavior stategy is stimulated and suppressed by other robot using communiation. Finally much stimulated strategy is adopted as a swarm behavior strategy. This control scheme is based on clonal selection and idotopic network hypothesis. And it is used for decision making of optimal swarm stragegy.

In this paper we discuss an algorithm to discriminate a garget under track against multiple acoustic counter-measure (ACM) sources, based on sequential testings of multiple hypotheses. The ACM sources are separated from the target under track and generate, while drifting, measurements with false range and Doppler information. The purpose of the ACM is to mislead the target tracking and to help the true target evade a pursuer. The proposed algorithm uses as a test statistic a function of the innovation sequences from extended Kalman filters to estimate the target dynamics and the drifting positions of the ACM sources. results of numerical experimenats are presented to show a performance profile of the proposed algorithm.

In this study, we implemented a scanning capacitance decimicron micorscope(SCdM) which scans a surface of the object mechanically in two or two point five dimensions with a stylus of size 0.2.mu.m. X-Y stage and stylus driving method are used as the scanning method, and VHD disk plate and IC chip are used as the object. Experimenal resutl of these object show that SCdM obtain 0.1.mu.m resolution power which exceeds that of optical microscope, and this microscope will be used as a powerful tool for inspecting ULSI pattern or biological data as a decimicron mcirocope which zoom a function of optical microscope and guide STM. The experimental system is composed of a VHD video disk method which captures the capacitance changes of the video disk suface and converts it into video signal.

This paper presents a high performance disparity extraction algorithm that generate a dense and accurate disparity map using low-resolution disparity histogram. Disparity distribution of background and object areas can besegmented from low-resolution disparity histogram. These information can be used to reduce the search area and search range of the high-resolution image resulting reliable disparity information in high speed. The computationally efficient matching pixel count(MPC) similarity measure technique is useed extensively toremove the redundancies inherent in the area-based matching method, and also results robust matching at the boundary region. Resulting maches are further improved using iterative support algorithm and post processing. We have obtained good results on randomdot stereogram and real images obtained in our carmera system.

This paper presents a fast motion estimation algorithm, 5DS, useful for video coding. We first try block matching to 4 directions(N, E, W, S) to estimate motions in this algorith, since most of motions in video are oriented to those direction, and then try one additional diagonal matching between the matching ponts having small MADs. It makesthis algorithm possible for searching through a diagonal direction which is not adequate to logarithmic (LOG) search algorithm. This proposed algorithm has almost same PSNR but, 1.9, 1.2 times faster than classical block matching methods such as three steps search(TSS) and LOG search algorithms.

This paper describes the classification of remotely sensed image data using fuzzy neural network, whose algorithm was obtained by replacing real numbers used for inputs and outputs in the standard back propagation algorithm with fuzzy numbers. In the proposed method, fuzzy patterns, generated based on the histogram ofeach category for the training data, are put into the fuzzy neural network with real numbers. The results show that the generalization and appoximation are better than that ofthe conventional network in determining the complex boundary of patterns.

In bitrate control of MPEG-2 TM5, $Q_{j}$, N-act, and mquant, of present macroblock are predicted from those of previous macroblock. It results in poor image quality because of abrups change of them. We proposed a method predicting $Q_{j}$, N-act, and mquant, of present macroblock by averaging those parameters of adjacent previous macroblocks. As a results, it shows improved PSNR compared to bitrate control of MPEG-2 TM5.TM5.

When we make a speaker adapted model using MAPE (maximum a posteriori estimation), the adapted model has one mixture in each state. This is because we cannot estimate a number of a priori distribution from a speaker-independent model in each state. If the model is represented by one mixture in each state, it is not well adadpted to specific speaker because it is difficult to represent various speech informationof the speaker with one mixture. In this paper, we suggest the method using several mixtures to well represent various speech information of the speaker in each state. But, because speaker-specific training dat is not sufficient, this method can't be used in every state. So, we make the number of mixtures in each state variable in proportion to the number of frames and to the determinant ofthe variance matrix in the state. Using the proposed method, we reduced the error rate than methods using one branch in each state.

We present a sequential factorization method using singular value decomposition (SVD) for recovering both the three-dimensional shape of an object and the motion of camera from a sequence of images. We employ paraperpective projection [6] for camera model to handle significant translational motion toward the camera or across the image. The proposed mthod not only quickly gives robust and accurate results, but also provides results at each frame becauseit is a sequential method. These properties make our method practically applicable to real time applications. Considerable research has been devoted to the problem of recovering motion and shape of object from image [2] [3] [4] [5] [6] [7] [8] [9]. Among many different approaches, we adopt a factorization method using SVD because of its robustness and computational efficiency. The factorization method based on batch-type computation, originally proposed by Tomasi and Kanade [1] proposed the feature trajectory information using singular value decomposition (SVD). Morita and Kanade [10] have extenened [1] to asequential type solution. However, Both methods used an orthographic projection and they cannot be applied to image sequences containing significant translational motion toward the camera or across the image. Poleman and Kanade [11] have developed a batch-type factorization method using paraperspective camera model is a sueful technique, the method cannot be employed for real-time applications because it is based on batch-type computation. This work presents a sequential factorization methodusing SVD for paraperspective projection. Initial experimental results show that the performance of our method is almost equivalent to that of [11] although it is sequential.

This paper presentsa new currnet control method ofthe six-pulse cycloconverter which is used as a variable speed drive system of a large capacity ac mortor. For a high performance control as a vector control, it is necessary that the output current control ofthe power converter has a good characteristic in transient state. A new proposed current control method is that the output current of a cycloconverter is followed after the current reference directly as fast as possible under any condition. Simultion results for the proposed new current control method are shown and its validity of the proposed method is confired.