This paper is proposed a Modified WLD (Weighted Levenshtein Distance) algorithm for processor desihn of code-string matching. A proposed MWLD (Modified Weighted Levenshtein Distance) algorithm is consist of 1-dimension bit-serial array processor to pattern matching using a Hamming Distance. The proposed processor is applied to recognition of character with real time input. The recognition rate of Hangul strokes is resulted to 98.65$\%$

In recent years, object-orientation is rising to notice as a new paradigm for developing software. This paper suggests the diagramming technique and a tool for developing C++ program effectively. This technique can represent the modularity and the interactions of classes definitely by emphasizing the characteristics of classes of C++. It can do the direct mapping from the logical idea to the physical screen image, so programmers can reuse the design resources in design phase as well as transforming the resources into chode in the implementation phase.

MR(Model Reduction) is presented in order to estimate the frequency of multiple sinusoids from the finite noisy data with the white or colored noises. MR, using the reduced rank models, is designed, appling the approximation of linear system to LP(Linear Prediction). The MR method is analyzed. Monte-carlo simulations are conducted for MR and Lp. The results are compared with in terms of mean, root-mean square and relative bias. MR eliminates effectevely the extremeous and exceptional poles appearing in LP and improves the accuracy of LP. Especially, MR gives promising results in short noisy measurements, low SNR's and colored noises. Power spectral density and angular frequency position are showed by figures, for examples. Finally, the new method is utilized to the communication and biomedical systems estimating the characteristics of the signal and the system identification modelling the dynamic systems from experimental data.

3 Dimensional measurement system using camera and laser slit-ray is studied. Precise calibration technique in this system is suggested. Calibration is accomplished with calibration die, calibration block and robot. For obtaining calibration parameters, the equations are solved using least square error method from a great many calibration points to reduce measuring error. Continuous measurement is possible for the object which is larger than one frame of camera. The efficiency and usability are proved by applying to the tire profile measuring system which measures tire profile using robot and this system.

In this paper,a new approach-using the linear movement of the lens location in a camera and focal distance in each location for the measurement of the depth of the 3-D object from several 2-D images-is proposed. The sharply focused edges are extracted from the images obtained by moving the lens of the camera, that is, the distance between the lens and the image plane, in the range allowed by the camera lens system. Then the depthin formation of the edges are obtained by the lens location. In our method, the accurate and complicated control system of the camera and a special algorithm for tracing the accurate focus point are not necessary, and the method has some advantage that the depth of all objects in a scene are measured by only the linear movement of the lens location of the camera. The accuracy of the extracted depth information is approximately 5% of object distances between 1 and 2m. We can see the possibility of application of the method in the depth measurement of the 3-D objects.

In the most studies of Korean character recognition so far, they first classify the characters to 6 types according to their structures and then recognize the characters by identifying their basic components named $'$jaso.$'$ In the study, we propose a method which recognizes the characters without using structure types and is applied to reading documents containing both Korean and Chinese characters. We first classify Korean and Chinese characters by using a modified SOFM model. Then we recognize the characters in each class by using an APC neural network which has the advantage of fast leaning speed and the capablity of additive learning. An experimental result demonstrated the usefulness of the approach with the recognition rate of $\%.$\%.

Fuzzy logic rule based controller has many desirable advantages, whih are simple to implement on the real time and need not the information of structure and dynamic characteristics of the system. Thus, nowadays, the scope of the application of the fuzzy logic controller becomes enlarged. But, if the controlled plant is a time-varying/nonlinear system, it is not easy to construct the fuzzy logic rules which need the knowledge of and expert. In this paper, an approach by which the logic control rules can be auto-generated using the genetic algorithm that is known to be very effective in the optimization problem will be proposed and the effectiveness of the proposed approach will be verified by computer simulation of the 2 d.o.f. planner robot.