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김용신(Yongseen Kim),김남호(Namho Kim),김지훈(Ji-Hoon Kim) 대한전자공학회 2015 대한전자공학회 학술대회 Vol.2015 No.6
Many artificial neural networks (ANN) have been implemented for various applications. However, handling large networks is still challenging because of its huge power and area overhead. In this paper, we propose the novel architecture which can support large-scale networks such as image processing as well as other various applications by dynamically decreasing the number of hardware neurons. While its learning capability is obtained from software using back propagation algorithm, the proposed architecture is exemplified by optical character recognition (OCR) system and implemented using 65nm CMOS process.