https://scholar.dgist.ac.kr/handle/20.500.11750/6124 2026-04-06T05:42:47Z https://scholar.dgist.ac.kr/handle/20.500.11750/58824 Title: Hardware accelerator for performing computation of deep neural network and electronic device including same Author(s): 노석환; 궁재하; 구자현 Abstract: A hardware accelerator includes a processing core including a plurality of multipliers configured to perform one-dimensional (1D) sub-word parallelization between symbols and mantissas of a first tensor and symbols and mantissas of a second tensor, a first processing device configured to operate in a two-dimensional (2D) mode of operation in which the first tensor and the second tensor are coupled to each other, and a second processing device configured to operate in a two-dimensional (2D) mode of operation in which the first tensor and the second tensor are coupled to each other. And a second processing device configured to operate in a three-dimensional (3D) operation mode in which the calculation results of the plurality of multipliers are accumulated in a channel direction, and then a result of accumulating the calculation results is output. https://scholar.dgist.ac.kr/handle/20.500.11750/58353 Title: 신경망 모델에 기반하여 고주파 생체 신호를 복원하는 방법 및 장치 Author(s): 강홍기; 홍나리; 진경환; 이정협; 궁재하; 이재원 Abstract: 본 개시의 일 실시 예에 따른 고주파 생체 신호를 복원하는 방법은 프로세서에 의해, 제1 생체 신호를 로딩하는 단계 및 저주파 신호인 제1 생체 신호를 제1 신경망 모델에 기반하여 고주파 신호인 제2 생체 신호로 변환하는 단계를 포함할 수 있다. https://scholar.dgist.ac.kr/handle/20.500.11750/58352 Title: 완화된 프루닝을 통한 행렬 데이터 처리 방법 및 그 장치 Author(s): 궁재하; 박준기; 김재준 https://scholar.dgist.ac.kr/handle/20.500.11750/57274 Title: A 3.3-To-11V-Supply-Range 10μW/Ch Arbitrary-Waveform-Capable Neural Stimulator with Output-Adaptive-Self-Bias and Supply-Tracking Schemes in 0.18μm Standard CMOS Author(s): Wie, Jeongyoon; Jung, Sangwoo; Seol, Taeryoung; Kim, Geunha; Lee, Sehwan; Jang, Homin; Kim, Samhwan; Shin, Yeon Jae; Jang, Jae Eun; Kung, Jaeha; George, Arup Kocheethra; Lee, Junghyup Abstract: Neurostimulation has emerged as the cornerstone that enables closed-loop brain-machine interfaces and targeted treatments for many neurological disorders. Regardless of the application, neurostimulators employ implanted electrodes to deliver charge pulses to tissues within safety limits to engender desired neural responses. However, as electrode-Tissue-impedance (ETI) varies widely (Fig. 1 (top)), neurostimulators should operate over a wide supply range to ensure both therapeutic effectiveness and safety [1]. When ETI is large, a higher supply is needed to provide adequate stimulation. However, when ETI is low, a low supply is necessary to minimize tissue damage from excessive electrical field and heat rise [1], [2]. Furthermore, power consumption during standby mode limited to under 10μ W/Ch ensures no tissue necrosis. Lastly, a stimulator capable of delivering arbitrary stimulation waveforms is also desirable for maximal efficiency and therapeutic effectiveness. © 2024 IEEE. 2024-04-23T15:00:00Z