A Korean word is composed of syllables. A Korean syllable is regarded as a random variable according to its probabilistic property in occurrence. A Korean syllable is divided into 'choseong', 'jungseong', and 'jongseong' which are regarded as random variables. We can consider teh conditional probatility of syllable as an index which represents the occurrence correlation between syllables in Korean words. Since the number of syllables is enormous, we use the conditional probability of a' choseong', a 'jungseong', and a 'jongseong' between syllables as an index which represents the occurrence correlation between syllables in Korean words. The length distribution of Korean woeds is computed according to frequency and to kind. Form the cumulative frequency of a Korean syllable computed from multi-syllable Korean woeds, all probabilities and conditiona probabilities are computed for the three random variables. The conditional probabilities of 'choseong'- 'choseong', 'jungseong'- 'jungseong', 'jongseong'-'jongseong', 'jongseong'-'choseong' between adjacent syllables in multi-syllable Korean woeds are computed.

In this paper, an efficient storage reclamation algorithm for RISC parallel processing in the object orented programming environments is presented. The memory management for the dynamic memory allocation and the frequent memory access in object oriented programming is the main factor that decreases RISC parallel processing performance. The proposed algorithm can be efficiently allocated the memory space of RISCy computer which is required the frequent memory access, so it can be increased RISC parallel processing performance. The proposed algorithm is verified the efficiency by implementing C language on SUN SPARC(4.3 BSD UNIX).

In this paper, we propose a graphic system for high speed generation of bitmap font data from the outline font data such as PostScript, etc. In desk-top publishing system. A VLSI chip called KAFOG was designed for the high-speed calculation of a cubic Bezier curve, which was implemented in 1.5\ulcorner CMOS gate array using 17,000 gates. A cubic Bezier curve is approximated by a set of line segments in KAFOG at the throughput of 250K curves per second with the clock frequency of 40 MHz. A prototype graphic system was developed using two MC6800 microprocessors and the KAFOG chip. Two microprocessors cooperate in a master and slave mode, and handshaking is used for communication between two processors. KAFOG chip, being controlled by the slave processor, operates as a coprocessor for the calculation of the outline font. The throughput of the prototype graphic system is 40 64$\times$64 outline fonts per sencond.

The symplified segmentation method was proposed for hardware implementation based on the human visual system. The segmentation method using fuzzy logic and just noticeable difference(JND) is composed of pre-filtering, initial segmentation and post processing. Experimental coding results show that reconstructed image using the proposed method is good on visual percerption even at a high compression ratio of 30:1.

This paper presents a new approach to explicityly use surface normal images (SNIs) in 3-D object model description and recognition procedure. The surface normal images of an object are defined as the projected images obtained from view angles facing normal to each surface of the object. The proposed approach can significantly alleviate the difficulty of obtaining correspondence between models and scene objects by explicitly providing a transform for the matching. The proposed approach is applied to the construction of a model-based 3-D object recognition system for the selected five objects. Synthetic images are used in the experiment to show the operation of the overall recognition system.

This paper develops a modified multilayer perceptron architecture which speeds up learning as well as the net's mapping accuracy. In Phase I, a cluster partitioning algorithm like the Kohonen's self-organizing feature map or the leader clustering algorithm is used as the front end that determines the cluster to which the input data belongs. In Phase II, this cluster selects a subset of the hidden layer nodes that combines the input and outputs nodes into a subnet of the full scale backpropagation network. The proposed net has been applied to two mapping problems, one rather smooth and the other highly nonlinear. Namely, the inverse kinematic problem for a 3-link robot manipulator and the 5-bit parity mapping have been chosen as examples. The results demonstrate the proposed net's superior accuracy and convergence properties over the original backpropagation network or its existing improvement techniques.