http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
자동 클럭 보정 기능을 갖춘 크리스털리스 클럭 합성기 설계
김지훈,김호원,이강윤,Jihun Kim,Ho-won Kim,Kang-yoon Lee 반도체공학회 2024 반도체공학회 논문지 Vol.2 No.3
본 논문은 32, 72, 80MHz 의 주파수에서 작동하는 블루투스 저에너지(BLE) 스마트 태그 애플리케이션용으로 설계된 보정 기능이 있는 레퍼런스 클럭 합성기(CR)에 대해 설명합니다. 기존 주파수 합성기와 달리 제안된 설계는 외부 소자가 필요하지 않습니다. 단일 종단 안테나를 사용하여 2.4GHz 신호에서 - 36dBm 의 최소 입력 전력을 수신하는 클럭 합성기(CR)는 저잡음 증폭기(LNA)를 통해 수신된 RF 신호를 처리하여 클럭을 합성합니다. 이 방식을 통해 시스템은 크리스털에 의존하지 않고 레퍼런스 클럭을 생성할 수 있습니다. 수신된 신호는 LNA 에 의해 증폭된 이후 16 비트 ACC(자동 클럭 보정) 회로에 입력됩니다. ACC는 수신된 신호의 주파수를 발진기 출력 주파수와 비교하여 주파수 계산 방법을 통해 32MHz 레퍼런스 클럭 합성을 용이하게 합니다. 발진기는 주파수 분배기가 있는 링 발진기(RO)를 사용하여 구성되며, 다양한 시스템 구성 요소에 대해 세 가지 주파수(32/72/80MHz)를 제공합니다. 제안된 주파수 합성기는 55nm CMOS 공정을 사용하여 구현되었습니다. This paper presents a crystal-less reference clock recovery (CR) frequency synthesizer with compensation designed for Bluetooth Low Energy (BLE) Smart-tag applications, operating at frequencies of 32, 72, and 80MHz. In contrast to conventional frequency synthesizers, the proposed design eliminates the need for external components. Using a single-ended antenna to receive a minimal input power of -36dBm at a 2.4GHz signal, the CR synthesizes frequencies by processing the RF signal received through a Low Noise Amplifier ( L N A ) . This approach allows the system to generate a reference clock without relying on a crystal. The received signal is amplified by the LNA and then input to a 16-bit ACC (Automatic Clock Compensation) circuit. The ACC compares the frequency of the received signal with the oscillator output signal, using the synthesis of a 32MHz reference clock through a frequency compensation method. The oscillator is constructed using a Ring Oscillator (RO) with a Frequency Divider, offering three different frequencies (32/72/80MHz) for various system components. The proposed frequency synthesizer is implemented using a 55-nm CMOS process.
김지훈,이대식,이민호,Kim, Jihun,Lee, Daesik,Lee, Minho 대한임베디드공학회 2016 대한임베디드공학회논문지 Vol.11 No.3
Lane detection is a widely researched topic. Although simple road detection is easily achieved by previous methods, lane detection becomes very difficult in several complex cases involving noisy edges. To address this, we use a Convolution neural network (CNN) for image enhancement. CNN is a deep learning method that has been very successfully applied in object detection and recognition. In this paper, we introduce a robust lane detection method based on a CNN combined with random sample consensus (RANSAC) algorithm. Initially, we calculate edges in an image using a hat shaped kernel, then we detect lanes using the CNN combined with the RANSAC. In the training process of the CNN, input data consists of edge images and target data is images that have real white color lanes on an otherwise black background. The CNN structure consists of 8 layers with 3 convolutional layers, 2 subsampling layers and multi-layer perceptron (MLP) of 3 fully-connected layers. Convolutional and subsampling layers are hierarchically arranged to form a deep structure. Our proposed lane detection algorithm successfully eliminates noise lines and was found to perform better than other formal line detection algorithms such as RANSAC
김지훈(JiHun Kim),최형연(Hyungyun Choi),이성준(Sungjun Lee),방용식(Yongsik Bang),임종수(Jongsu Lim) 한국자동차공학회 2015 한국자동차공학회 부문종합 학술대회 Vol.2015 No.5
Car collision analysis using a computer simulation is a method that can dramatically reduce the time and cost compared to Sled test. But this computer simulation analysis is very difficult and hard to make reliable result. We accomplished material property test for foam, padding foam, trim cover to make a seat model considered manufacturing. And we simulated the process of the trim cover surrounding the foam to applying pre-stress. We seated HRMD to check the H-point, seat back angle and backset before BioRID II seated in computer analysis program. We tested rear collision test according to Euro NCAP. We attached FSR sensor and accelerometer in headrestraint, seat back and seat cushion to check the seat pressure map, seat acceleration and dummy injury. We were compared test data and finite element model.
김지훈(Kim Jihun) 대한의학유전학회 2014 대한의학유전학회 학술대회 논문집 Vol.1 No.1
태아 염색체이상의 산전선별검사(prenatal screening)는 침습적 검사와 비침습적 검사가 사용된다. 침습적 검사로는 양수천자(Amniocentesis), 융모막 융모 검사(Chorionic Villus Sampling) 등이 있고 높은 정확성으로 확진검사로 사용되나, 태아손실(1-2%) 위험성이 있다.