In this paper, we show that Petri nets can be applied to design and reliability analysis of concurrent, parallel and embedded mode system such as a lift system that is familiar to our daily life. Modeling the behavioral characteristics of the lift system we extend the standard Petri nets by nadditionally constant timed transition, fault transition, stochastic imed ttransition and conditional transition concepts. Likewise, we present esults of rdesign and analysis of the system. This method can be applied to esign and danalysis of any other concurrent systems.

A multi-font, multi-size and high speed character recognition system is designed. The design principles are simpilcity of algorithm, adaptibility, learnability, hierachical data processing and attention by feed back. For the multi-size character recognition, the extracted character images are normalized. A hierachical classifier classifies the feature vectors. Feature is extracted by applying the directional receptive field after the directional dege filter processing. The hierachical classifier is consist of two pre-classifiers and one decision making classifier. The effect of two pre-classifiers is prediction to the final decision making classifier. With the pre-classifiers, the time to compute the distance of the final classifier is reduced. Recognition rate is 95% for the three documents printed in three kinds of fonts, total 1,700 characters. For high speed implemention, a multiprocessor system with the ring structure of four transputers is implemented, and the recognition speed of 30 characters per second is aquired.

This paper suggests the new high-speed input/output techniques in a shared memory multiprocessor system. The high-speed I/O processor which can connect the different kinds of large sized I/O periperal devices, the communication protocol to the main processing units for I/O operations, and the job scheduling scheme are addressed. This paper also introduces the disk cache technique which supports the slow I/O devices comparing with the main processing units. These techniques were implemented in the TICOM system. The performance evaluation statistics were collected and analyzed for the suggested high-speed I/O processing techniques. These statistics show the superiority of the suggested techniques.

Lock mechanism is essential for synchronization on the multiprocessor systems. Lock mechanism needs to reduce the time for lock operation in low lock contention. Lock mechanism must consider the case of the high lock contention. The conventional lock control scheme in memory results in the increase of bus traffic and memory utilization in lock operation. This paper suggests a lock scheme which stores the lock data in cache and manages it efficiently to reduce the time spent in lock operation when the lock contention is low on a multiprocessor system built on HiPi-bus(Highly Pipelined bus). This paper also presents the design of the HIPi-CLOCK (Highly Pipelined bus Cache LOCK mechanism) which transfere the data from on cache to another when the lock contention is high. The designed simulator compares the conventional lock scheme which controls the lock in memory with the suggested HiPi-CLOCK scheme in terms of the RMW(Read-Modify-Write) operation time using simulated trace. It is shown that the suggested lock control scheme performance is over twice than that of the conventional method in low lock contention. When the lock contention is high, the performance of the suggested scheme increases as the number of the shared lock data increases.

In this paper, we will present an array processor for implementation of digital neural networks. Back-propagation model can be formulated as a consecutive matrix-vector multiplication problem with some prespecified thresholding operation. This operation procedure is suited for the design of an array processor, because it can be recursively and repeatedly executed. Systolic array circuit architecture with Residue Number System is suggested to realize the efficient arithmetic circuit for matrix-vector multiplication and compute sigmoid function. The proposed design method would expect to adopt for the application field of neural networks, because it can be realized to currently developed VLSI technology.

This paper describes the development of a speaker-dependent isolated word recognizer as applied to voice dialing in a car noise environment. for this purpose, several methods to improve performance under such condition are evaluated using database collected in a small car moving at 100km/h The main features of the recognizer are as follow: The endpoint detection error can be reduced by using the magnitude of the signal which is inverse filtered by the AR model of the background noise, and it can be compensated by using variants of the DTW algorithm. To remove the noise, an autocorrelation subtraction method is used with the constraint that residual energy obtainable by linear predictive analysis should be positive. By using the noise rubust distance measure, distortion of the feature vector is minimized. The speech recognizer is implemented using the Motorola DSP56001(24-bit general purpose digital signal processor). The recognition database is composed of 50 Korean names spoken by 3 male speakers. The recognition error rate of the system is reduced to 4.3% using a single reference pattern for each word and 1.5% using 2 reference patterns for each word.

The motion vector estimation and motion boundary detection have been briskly studied since they are an important clue for analysis of object structure and 3-d motion. The purpose of this researches is more exact estimation, but there are two main causes to make inaccurate. The one is the erroneous measurement of gradients in brightness values and the other is the blurring of motion boundries which is caused by the smoothness constraint. In this paper, we analyze the gradient measurement error of conventional methods and propose new technique based on it. When the proposed method is applied to the motion boundary detection in Schunck and motion vector estimation in Horn & Schunck, it is shown to have much better performance than conventional method is some artificial and real image sequences.

Automatic image recognition system is essential for a better man-to machine interaction. Because of the noise and deformation due to the sensor operation, it is not simple to build an image recognition system even for the fixed images. In this paper neural network which has been reported to be adequate for pattern recognition task is applied to the fixed and variational(rotation, size, position variation for the fixed image)recognition with a hope that the problems of conventional pattern recognition techniques are overcome. At fixed image recognition system. ART model is trained with face images obtained by camera. When recognizing an matching score. In the test when wigilance level 0.6 - 0.8 the system has achievel 100% correct face recognition rate. In the variational image recognition system, 65 invariant moment features sets are taken from thirteen persons. 39 data are taken to train multi-layer perceptron and other 26 data used for testing. The result shows 92.5% recognition rate.

A nonlinear method for directional information processing is introduced, along with an application of directional feature enhancement. In this method, an input is convolved with a 2-D ong, norrow kernel, which is rotated through 360 degree, continuously or discretely in a large number of steps. An output is given by some function of the convolution results. Linear features that are aligned with the kernel are enhanced, otherwise, removed or suppressed. The method presented is insensitive to variation in the dimension of linear features to be processed and preserves a good enhancement capability even for an image characterized by low contrast and spatially varying brightness in noisy backgroung. Effects of the kernel legnth and width on the performance are discussed. A possible hybrid optical-electronic implementation is also discussed.

Because of the complexity, nonlinearity and long-time delay of power plant, the star-up operation of a fossil power plant is very difficult to automate. So the start-up operation is always carried out by the skilled human operators, who utilize their knowledges and experiences for the predesigned start-up schedules and procedures. In this paper, a fuzzy logic controller is designed for the start-up operation of the power plant. And the operators experiences are modeled in terms of fuzzy sets and variables. To validate the controller, a drum-type boiler of the Seoul Power Plant is constructed via the signal flow diagram. Using the model, the suggested automatic start-up operation is verified, and the results are also presented.