• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.181-186
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• 1992

Many real-world problems are concerned with estimation rather than classification. This paper presents an adaptive technique to estimate the mechanical properties of materials from acoustoultrasonic waveforms. This is done by adapting a piece-wise linear approximation technique to a multi-layered neural network architecture. The piece-wise linear approximation network (PWLAN) finds a set of connected hyperplanes that fit all input vectors as close as possible. A corresponding architecture requires only one hidden layer to estimate any curve as an output pattern. A learning rule for PWLAN is developed and applied to the acousto-ultrasonic data. The efficiency of the PWLAN is compared with that of classical backpropagation network which uses generalized delta rule as a learning algorithm.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.368-371
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• 1999

In this paper, we propose a neural network processor architecture with on-chip learning and with reconfigurability according to the data dependencies of the algorithm applied. For the neural network model applied, the proposed architecture can be configured into either SIMD or SRA(Systolic Ring Array) without my changing of on-chip configuration so as to obtain a high throughput. However, changing of system configuration can be controlled by user program. To process activation function, which needs amount of cycles to get its value, we design it by using PWL(Piece-Wise Linear) function approximation method. This unit has only single latency and the processing ability of non-linear function such as sigmoid gaussian function etc. And we verified the processing mechanism with EBP(Error Back-Propagation) model.

• Journal of Welding and Joining
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• v.8 no.2
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• pp.58-69
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• 1990

In conventional arc welding, position error of the weld torch with respect to the weld seam and variation of groove dimension are induced by inaccurate fitup and fixturing. In this study, a vision system has been developed to recognize and compensate the position error and dimensional inaccuracy. The system uses a structured laser light illuminated on the weld groove and perceived by a C.C.D camera. A new algorithm to detect the edge of the reflected laser light is introduced for real time processing. The developed system was applied to arbitarary weld paths with various types of joint in arc welding process. The experimental results show that the proposed system can detect the weld groove parameters within good accuracy and yield good tracking performance.