A multiprocessor system for high-speed processing of hybrid image coding algorithms such as H.261, MPEG, or Digital HDTV is presented in this study. Using a combination of highly parallel 32-bit microprocessor, DCT(Discrete Cosine Transform), and motion detection processor, a new processing module is designed for the implementation of high performance coding system. The sysyem is implemented to allow parallel processing since a single module alone cannot perform hybrid coding algorithms at high speed, and crossbar switch is used to realize various parallel processing architectures by altering interconnections between processing modules within the system.

Motion picture algorithms are realized on the multiprocessor system presented in the Study I. For the most efficient processing of the algorithms, pipelining and geometrical parallel processing methods are employed, and processing time, communication load and efficiency of each algorithm are compared. The performance of the implemented system is compared and analysed with reference to MPEG coding algorithm. Theoretical calculations and experimental results both shows that geometrical partitioning is a more suitable parallel processing algorithm for moving picture coding having the advantage of easy algorithm modification and expansion, and the overall efficiency is higher than pipelining.

In this paper, a driver system is designed and implemented to achieve 4-level gray scale CH TFEL(Thin Film ElectroLuminescent) flat panel display. To implement the driver system, commercial EL driver IC chips are used to apply high voltage pulses to the EL panel and a high voltage switching circuit is designed for the EL driver IC. A new method of reducing storage delay time of transistor is proposed to obtain a reliable switching circuit. The controller for EL driver and switching circuit is also designed. The designed driving scheme applicable to EL display with 4-level gray scale is based on the linear characteristics of brightness vs. frequency of AC TFEL. By experiment, it has been shown that the brightness of AC TEFL display with the implemented driving system is controlled by the level of gray scale.

In this paper, a new speech enhancement method for speech signal corrupted by environmental noise is proposed. Two signals are obtained from the microphone and from the accelerometer attached to the neck, respectively. Since two signals are generated from same source signal, both signals are closely correlated. And environmental noise has no effect on the accelerometer signal. The speech enhancement system identifies the optimum linear system between two signals on the basis of the dependence between the signals. The enhanced speech can be obtained by filtering the noise-free accelerometer signal. Since the characteristcs of the speech signal and environmental noise are changing with time, adaptive filtering system has to be used for characterizing the time-varing system. Simulation results show 7dB enhancement with 0dB speech signal level relative to the white noise.

In this paper, we evaluate the quality of synthesized speech by rule using the LPC CD as a objective measure, and then compare the test result with the subjective one. Speech used for the test consists of 108 words which are selected by word construction method using Korean attribute and frequency distribution, synthesized by demi-syllable rule. By evaluating the quality of synthesized speech by reule objectively, we have tried to resolve the problems such as lots of evaluation time, expansion of test scale, and variables of analysis result arised by subjective measure. We have, also, proved the validity of the objective test using the LPC CD, by comparing intelligibility which is the index for the subjective quality evaluation of synthesized speech by rule with MOS. From this results, we can provide a guide for quality assessment that would be useful in the R&D of synthesis method and the commercial products using synthesized speech.

The problem of trajectory planning in two redundant robot systems is considered. The trajectory of each robot for the cooperative task is generated so that the robots assume their optimal configurations while following a given desired task. The cooperative task compatibility in and the weighted sum of manipulabilities are proposed and investigated as quality measures. The cooperative task compatibility includes the velocity and force transmission charateristics to the task requirements and so it measures the compatibilities of robot postures with respect to a given task. The weighted sum of manipuabilities of robot postures with respect to a given task. The weighted sum of manipulabilities is also considered as a quality measure since it is helpful to avoid singularities. The usefulness of the cooperative task compatibility and the weighted sum of manipulabilities are shown by computer simulation studies.

This paper describes implemation of 'General-purpose ETRI MAP interface module' (GEM) for Mini-MAP network. GEM operates as a Mini-MAP node in our FA system. To communicate between GEM and programmable devices(PD) such as PLC and CNC, serial communication is used. Application programs of a MiNi-MAP host system control and monitor programmable devices via GEM. GEM is implemented and tested on the basis of the MAP 3.0. TBC in the Nini-MAP board performs the function of the MAC sublayer. The LLC sublayer is implemented according to the specification of Class 3 that includes Type 1 and 3. And the MMS services are designed within the scope of implementation class MAP3. All the softwares are implemented under the real-time multitask OS for real-time application of the Mini-MAP and they are loaded into PROMs at the network board of GEM. We tested the LLC functions to make use of a protocol analyzer for the token-passing protocol. Also the MMS conformance test was carried out by exchanging primitives between GEM and a MMS product that had already passed the conformance test. Therefore GEM is proposed as a network tool of Computer Integrated Manufacturing (CIM) to integrate PDs which don't support MAP functions.

In this paper we propose a design of a digital neuron processor using the residue number system for efficient matrix.vector multiplication involved in neural processing. Since the residue number system needs no carry propagation for modulus operations, the neuron processor can perform multiplication considerably fast. We also propose a high speed algorithm for computing the sigmoid function using the specially designed look-up table. Our method can be implemented area-effectively using the current technology of digital VLSI and siumlation results positively demonstrate the feasibility of our method. The proposed method would expected to adopt for application field of digital neural network, because it could be realized to currently developed digital VLSI Technology.

In this paper, we present a method to solve a convexly combined fuzzy relational equation with generalized connectives. For this, we propose a neural network whose structure represents the fuzzy relational equation. Then we derive a learning algorithm by using the concept of back-propagation learning. Since the proposed method can be used for a general form of fuzzy relational equations, such fuzzy max-min or min-max relational equations can be treated as its special cases. Moreover, the relational structure adopted in the proposed neurocomputational approach can work in a highly parallel manner so that real-time applications of fuzzy sets are possibles as in fuzzy logic controllers, knowledge-based systems, and pattern recognition systems.

This paper presents the two-stage neural network method for efficient channel assignment of cellular mobile radio network. The first stage decomposes the region into non-adjacent groups of cells and the second stage assigns channels to the decomposed groups. The neural network model is tested with an experimental system of eighteen channels dedicated for nineteen hexagonal-cell region. When radom call requests of average density of 2 Erl/Cell to 8 Erl/Cell are presented, the real-time channel assignment method reduces the call-blocking rate up to 16% against the existing SCA(Static Channel Assignment) method.

IPA(interpattern association) model is a method of feature extraction using a neural network. Even in the case that the reference patterns are simuklar to one another, this model can recover the reference patterns effectively. However, when the pattern whose feature pixels are lost is used as input, this model can not guarantee perfect recovery of the reference pattern. It is proposed a improved interpattern association(IPA) model for the feature extraction using neural network. The improved IPA model that combines the first interconnection weight matrix of the IPA model with the second additional weight matrix is proposed here to overcome the recovery problem of the original IPA model. The results of computer simulation and optical experiment are advanced.