• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.506-507
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• 2007

Lateral Information Propagation Neural Networks (LIPN) is proposed for on-line interpolation. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.05b
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• pp.119-123
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• 2002

A new modular Lateral Information Propagation Networks(LIPN) has been designed. The LIPN has shown to be useful for reconstruction of information[3]. The problem is the fact that only the small number of nodes can be implemented in a IC chip with the circuit VLSI technology. The proposed modular architecture is propagated the neural network through inter module connections. For such inter module connections, the host (computer or logic) mediates the exchange of information among modules. Also border nodes in each module have capacitors for temporarily retaining the information from outer modules. The LIPN with $4{\times}4$ modules has been designed and simulation of interpolation with the designed LIPN has been done.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.04c
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• pp.54-57
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• 2008

A new modular Lateral Information Propagation Networks can be implemented in a IC chip with the circuit VLSI technology for detection of bad materials. The proposed modular architecture is propagated the neural network through inter module connections. For such inter module connections, the host(computer or logic) mediates the exchange of information among modules. Also border nodes in each module have capacitors for temporarily retaining the information from outer modules. For detecting of Faulty Insulator, $4\;{\times}\;4$ neural network modules has been designed and simulation of interpolation with the designed networks has been done.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.461-464
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• 1998

Lateral Information Propagation Neural Networks (LIPN) is proposed for on-line interpolation. The proposed neural network technique is the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interpolation is achieved. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed. 1-D LIPN hardware has been implemented with general purpose analog ICs to test the interpolation capability of the proposed neural networks. Experiments with static and dynamic signals have been done upon the LIPN hardware.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2206-2208
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• 1998

The modular Lateral Information Propagation Networks(LIPN) has been designed. The LIPN has shown to be useful for interpolation of information[3]. The problem is the fact that only the small number of nodes can be implemented in a IC chip with the circuit VLSI technology. The proposed modular architecture is for enlarging the neural network through inter module connections. For such inter module connections, the host(computer or logic) mediates the exchange of information among modules. Also border nodes in each module have capacitors for temporarily retaining the information from outer modules. The LIPN with $4{\times}4$ modules has been designed and simulation of interpolation with the designed LIPN has been done.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2002.07b
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• pp.1097-1102
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• 2002

For detecting of Faulty Insulator, a new Lateral Information Propagation Networks (LIPN) has been proposed. Energized insulator is reduced the rate of insulation extremely, and taken the results dirty and injured. It is necessary to be actions that detect the faulty insulator and exchange the new one. And thus, we have designed the LIPN to be detected that insulators by the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interpolation is achieved. Through several simulation experiments,real time reconstruction of the nonlinear image information is processed.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.11b
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• pp.7-12
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• 2004

New modular Lateral Information Propagation Networks(LIPN) has been designed. The LIPN has shown to be useful for interpolation of information[3]. The problem is the fact that only the small number of nodes can be implemented in a IC chip with the circuit VLSI technology. The proposed modular architecture is for enlarging the neural network through inter module connections. For such inter module connections, the host(computer or logic) mediates the exchange of information among modules. Also border nodes in each module have capacitors for temporarily retaining the information from outer modules. Simulation of interpolation with the designed LIPN has been done through various experiments.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2546-2549
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• 2004

For Reduction of Power-Loss, a new Lateral Information Propagation Networks(LIPN) has been proposed. Damaged insulator is reduced the rate of insulation extremely, and taken the results dirty and injured. It is necessary to be actions that detect the damaged insulator and exchange the new one. And thus, we have designed the LIPN to be detected that insulators by the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interrelation is achieved. Through the results of simulation experiments, we difine the ability of real-time detecting the damaged insulators.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2007.11a
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• pp.508-509
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• 2007

For the safty driving of an automobile which is become individual requisites, a new Neural Network algorithm which recognized the load vehicles in real time is proposed. The proposed neural network technique is the real time computation method through the inter-node diffusion. The most reliable algorithm derived for real time recognition of vehicles, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2276-2279
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• 2002

For detecting of Energized Insulator, a new Lateral Information Propagation Networks(LIPN) has been proposed. Faulty insulator is reduced the rate of insolation extremely, and taken the results dirty and injured. It is necessary to be actions that detect the faulty insulator and exchange the new one. And thus, we have designed the LIPN to be detected that insulators by the real time computation method through the inter-node diffusion. In the network, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. Information propagates among neighbor nodes laterally and inter-node interpolation is achieved. Through the results of simulation experiments, we define the ability of real-time detecting the faulty insulators.