• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.1801-1802
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• 2007

자기 연관 시계열 신경망을 이용하여 식각종말점 패턴-기반 플라즈마 상태를 진단하는 방법을 제안한다. 식각종말점 패턴은 Oxide 박막의 식각공정 중 Optical Emission Spectroscopy를 이용하여 수집하였으며, 역전파 신경망을 이용하여 진단 모델을 개발하였다. 진단 모델은 단일 신경망과 모듈러신경망을 이용하여 개발하였으며, 비교평가결과 모듈러 신경망이더 우수한 성능을 보였다.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.25-30
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• 2005

In this paper, we analyzed and compared the performances of modular FFMLP(feedforward multilayer perceptron) and SVUT(Support Vector Machine) for the large-set classification problems. Overall, SVM dominated modular FFMLP in the correct recognition rate and other aspects Additionally, the recognition rate of SVM degraded more slowly than neural network as the number of classes increases. The trend of the recognition rates depending on the rejection rate has been analyzed. The parameter set of SVM(kernel functions and related variables) has been identified for the large-set classification problems.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.563-574
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• 2000

Recognition of numeral fields is a very important task for many document automation applications. Conventional methods are based on the two-steps process, segmentation of touching numerals and recognition of the individual numerals. However, due to a large variation of touching types this approach has not produced a robust result. In this paper, we present a new segmentation-free method for recognizing the two touching numerals. In this approach, two touching numerals are regarded as a single pattern coming from 100 classes ('00', '01', '02', ..., '98', '99'). For the test set, we manually extract two touching numerals from the data set of NIST numeral fields. Due to the limitation of conventional neural network in case of large-set classification, we use a modular neural network and Drove its superiority through recognition experimen.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.6
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• pp.56-68
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• 2003

Difficult problems In implementing digital neural network hardware are the extension of synapses and the programmability for relocating neurons. In this paper, the structure of a new hardware is proposed for solving these problems. Our structure based on traditional SIMD can be dynamically and easily reconfigured connections of network without synthesizing and mapping original design for each use. Using additional modular processing unit the numbers of neurons find synapses increase. To show the extensibility of our structure, various models of neural networks : multi-layer perceptrons and Kohonen network are formed and tested. The performance comparison with software simulation shows its superiority in the aspects of performance and flexibility.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.1
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• pp.25-30
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• 2000

Hangul is regarded as one of the difficult character set due to the large number of classes and the shape similarity among different characters. Most of the conventional researches attempted to recognize the 2,350 characters which are popularly used, but this approach has a problem or low recognition performance while it provides a generality. On the contrary, recognition of a small character set appearing in specific fields like postal address or bank checks is more practical approach. This paper describes a research for recognizing the handwritten Hangul characters appearing in monetary fields. The modular neural network is adopted for the classification and three kinds of feature are tested. The experiment performed using standard Hangul database PE92 showed the correct recognition rate 91.56%.

• Korean Journal of Cognitive Science
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• v.7 no.1
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• pp.75-84
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• 1996

In this paper we emphasize the importance of architectural aspects of designing a handwritten numeral recognition program. and describe two architectural design.First, we describe the modular design of a numeral recognition program, and mention its advantages.In this design, a recognizer is composed of 10 binary subrecognizers each of which is responsible for only one class.Rule-based training and neural-based training are presented.Second, we connect two(or more)recognizers serially which we call pipelining connection.The second recognizer may act as verifier for the patterns recognized by the forst recognizer, or as second chance recognizer for the patterns rejected by the first recognizer.Our experimental results obtained till now show the merits of the proposed architectural designs.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.18 no.3
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• pp.1-6
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• 2022

Ground source heat pump (GSHP) system is highly efficient and environment-friendly and supplies heating, cooling and hot water to buildings. For an optimal design of the GSHP system, the ground thermal properties should be determined to estimate the heat exchange rate between ground and borehole heat exchangers (BHE) and the system performance during long-term operating periods. However, the process increases the initial cost and construction period, which causes the system to be hindered in distribution. On the other hand, much research has been applied to the artificial neural network (ANN) to solve problems based on data efficiently and stably. This research proposes the predictive performance model utilizing ANN considering local characteristics and weather data for the predictive performance model. The ANN model predicts the entering water temperature (EWT) from the GHEs to the heat pump for the modular GHEs, which were developed to reduce the cost and spatial disadvantages of the vertical-type GHEs. As a result, the temperature error between the data and predicted results was 3.52%. The proposed approach was validated to predict the system performance and EWT of the GSHP system.

• The Journal of Information Technology
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• v.4 no.4
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• pp.51-63
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• 2001

Residue Number System has carry free operation and parallelism each modulus, So it is used for special purpose processor such as Digital Signal Processing and Neuron Processor. Magnitude comparison and sign detection are in need of Mixed Radix Conversion, and these operations are impediment to improve the operation speed. So in this Paper, MRC(Mixed Radix Converter) is designed using modified partitioned residue to speed up the operation of MRC, so it has progressed maximum twice operation time but increased the size of converter comparison to other converter.