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2nd International Conference on Electrical Engineering and Control Science, IC2ECS 2022

作者： Ran, Qianfan Zhang, Xudong Song, Chaoyang Li, Yuan Lin, Zhihong Chiang, Patrick Yin Fudan University State Key Laboratory of ASIC and System Shanghai China

ISBN: (纸本)9798350399165

Nowadays, low power consumption is one of the key developments in mobile internet-of-Things (IoT) devices proximity-detection. A low power monolithic CMOS optical sensor is presented in this article. The prototype sensor uses an auto-zero and correlated double sampling (CDS) based sample and hold (S/H) stage, which reduces low frequency noise as well as the op-Amp DC offset and photodiode (PD) dark current and also serves as a single-ended-To-differential converter. A third-order single-bit delta sigma ADC is implemented to attain high resolution proximity sensing. The optical sensor is fabricated with a 0.18 m CMOS process. The die size is 0.7∗1.2 mm2 and the chip scale package dimensions are only 0.7 mm3, showing high industrial design flexibility of sensor apertures sizes and shapes. The sensor draws an average current of 200 A from a 1.8 V supply during the active state. Tested under a 90% reflectance panel, the measurement results show a proximity distance of 20 mm and a resolution of 0.5 mm, which makes it a practical approach to proximity sensing in IoT devices. © 2022 IEEE.

关键词： Internet of things

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High Performance Injection-Locked PLL Architectures: An Overview 7

High Performance Injection-Locked PLL Architectures: An Over...

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7th International Conference on Integrated Circuits and Microsystems, ICICM 2022

作者： Jin, Zhaoji Yi, Ting Fudan University State Key Laboratory of ASIC and System Shanghai China

ISBN: (纸本)9781665460439

Low jitter phase locked loops (PLL) are widely used as clock generators and play a very critical role in various applications such as serial link or data converter systems. On the basis of conventional PLLs, researchers have invented sub-sampling, injection locking, and other techniques to improve the performance of PLL with constrained power and area. The injection-locked PLL (ILPLL) reduces the clock jitter by eliminating the accumulated jitter periodically. Because of the simple structure, the ILPLL has become the research focus in recent years. This paper reviews the development and application scenarios of ILPLLs. © 2022 IEEE.

关键词： Phase locked loops

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A 130 Three-Step DT Incremental ADC Achieving 107.6dB DR and 99.3dB SNDR with Zoom and Extended-Range Counting 48

A 130 Three-Step DT Incremental ADC Achieving 107.6dB DR and...

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48th IEEE European Solid state Circuits Conference, ESSCIRC 2022

作者： Fang, Lairong Li, Yijie Zhang, Yao Zhang, Shuwen Zeng, Xiaoyang Hong, Zhiliang Xu, Jiawei State Key Laboratory of ASIC and System Fudan University Shanghai China

ISBN: (纸本)9781665484947

This paper presents an incremental \Delta\Sigma ADC (IADC) utilizing a three-step conversion. By combining the zoom-in and extended-range (ER) counting techniques, the IADC significantly reduces the oversampling ratio (OSR) and power consumption of a standard incremental \Delta\Sigma counterpart. Clocked at 512kHz, the prototype IADC achieves a 107.6dB DR, a 104.9dB peak SNR, and a 99.3dB peak SNDR for a conversion rate of 2kS/s while consuming 130{\mu W} from a 1.8V supply. This corresponds to a state-of-The-Art Schreier FoMDR of 176.5dB. © 2022 IEEE.

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High Precision Voltage Reference for ADC: Review and Design Methodology 7

High Precision Voltage Reference for ADC: Review and Design ...

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7th International Conference on Integrated Circuits and Microsystems, ICICM 2022

作者： Tian, Hongyu Yi, Ting Fudan University State Key Laboratory of ASIC and System Shanghai China

ISBN: (纸本)9781665460439

High resolution analog-to-digital converters (ADCs) impose stringent accuracy requirements for the voltage reference, in terms of low temperature coefficient (TC), low noise, absolute accuracy and high driving capability. This paper reviews state-of-the-art circuit design techniques to implement a high precision ADC reference and the methodology to optimize the parameter metrics. © 2022 IEEE.

关键词： Temperature

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A review of ToF-based LiDAR

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Journal of Semiconductors 2024年第10期45卷 7-19页

作者： Jie Ma Shenglong Zhuo Lei Qiu Yuzhu Gao Yifan Wu Ming Zhong Rui Bai Miao Sun Patrick Yin Chiang The College of Electronics and Information Engineering Tongji UniversityShanghai 200092China State Key Laboratory of ASIC&System Fudan UniversityShanghai 201203China School of Electrical and Electronic Engineering Nanyang Technological UniversitySingapore Lyne Technologies Shanghai 201203China

In recent years,propelled by the rapid iterative advancements in digital imaging technology and the semiconductor industry,encompassing microelectronic design,manufacturing,packaging,and testing,time-of-flight(ToF)-based imaging systems for acquiring depth information have garnered considerable attention from both academia and *** technology has emerged as a focal point of research within the realm of 3D *** to its relatively straightforward principles and exceptional performance,ToF technology finds extensive applications across various domains including human−computer interaction,autonomous driving,industrial inspection,medical and healthcare,augmented reality,smart homes,and 3D reconstruction,among ***,the increasing maturity of ToF-based LiDAR systems is evident in current *** paper comprehensively reviews the fundamental principles of ToF technology and LiDAR systems,alongside recent research *** elucidates the innovative aspects and technical challenges encountered in both transmitter(TX)and receiver(RX),providing detailed discussions on corresponding ***,the paper explores prospective avenues for future research,offering valuable insights for subsequent investigations.

关键词： time of flight light detection and ranging transmitter receiver

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Periodic Analysis of Adaptive LMS Filter in TIADC 15

Periodic Analysis of Adaptive LMS Filter in TIADC

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15th IEEE International Conference on asic, asicON 2023

作者： Li, Jiankun Lin, Zepeng Ye, Fan Fudan University College of Microelectronics Shanghai China Fudan University State Key Laboratory of ASIC and System Shanghai China

ISBN: (纸本)9798350312980

A periodic analysis of LMS adaptive filter in TI-ADC is presented. TI-ADC is a efficient technique to reach high sampling frequency but mismatches among different sub-ADCs influence its performance. LMS adaptive filter is a finite impulse response (FIR) filter which adapt itself to different inputs once implemented. To analyse SFDR performance of LMS filter in time domain, converged weigh vector and its analysis frequency domain are done theoretically and emulationally. Simulation shows that our theoretical analysis is consistent with the practical results that the useful range of SFDR performance is only negatively related to filter length if sampling frequency is constant. Further, it is concluded that there is a trade-off between maximum of SFDR in LMS filter and its useful range in terms of frequency. © 2023 IEEE.

关键词： adaptive filter LMS TI-ADC

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Knowledge-based neural network SPICE modeling for MOSFETs and its application on 2D material field-effect transistors

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Science China(Information Sciences) 2023年第2期66卷 227-236页

作者： Guodong QI Xinyu CHEN Guangxi HU Peng ZHOU Wenzhong BAO Ye LU State Key Laboratory of ASIC and System School of Information Science and TechnologyFudan University State Key Laboratory of ASIC and System School of Microelectronics Fudan University Zhangjiang Fudan International Innovation Center Fudan University

As the traditional scaling of silicon metal-oxide-semiconductor field-effect transistors（MOSFETs） reaches its physical limit, research efforts on novel semiconductor devices are increasingly desired. To enable the joint optimization of early-stage circuit design and process of novel devices, the rapid creation of an accurate compact model of these devices with the capability to cover process variations is required. In this work, a knowledge-based neural network（KNN） modeling method is proposed. This method separates the geometrical variables from the other input variables of the device, where the geometrical variables are modeled with physics-based analytical equations, while the remaining part is modeled by an artificial neural network. The KNN model takes advantage of the automated numerical fitting capability of the neural network and the geometrical scalability from device physics. The created KNN model is first validated with silicon MOSFET data from the industry standard BSIM6 and shows more than 20% accuracy improvement as compared with the traditional neural network model. Furthermore, MoS2field-effect transistors and circuits,such as ring oscillators, standard cells, and logic functional circuits, are experimentally fabricated for model verification. The results show that the KNN model is capable of predicting the electrical characteristics of devices beyond the measurement geometry and facilitates the accurate simulations of statistical circuits with respect to experimental data. This work paves the way for future circuit designs and simulations of novel semiconductor devices.

关键词： knowledge-based neural network MOSFET 2D material FETs Monte Carlo simulations circuit benchmark

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A Comprehensive and Efficient Instruction-level Testing Method for Processor 17

A Comprehensive and Efficient Instruction-level Testing Meth...

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17th IEEE International Conference on Solid-state and Integrated Circuit Technology, ICSICT 2024

作者： Yang, Zixin Wei, Zhichao Luo, Huanlin Wang, Jian Lai, Jinmei School of Microelectronics Fudan University State Key Laboratory of ASIC and System Shanghai201203 China Shanghai Academy of Spaceflight Technology Shanghai201109 China

ISBN: (纸本)9798350361834

Testing of the processor is crucial, which necessitates a comprehensive test set to ensure an efficient and thorough coverage. We herein propose an Equivalence Class Partitioning and Boundary Value Analysis (ECP-BVA) constrained instruction stream generation method on coverage-guided fuzzing (CGF). The updated ECP-BVA constraints mutate the instruction field to maximize the coverage metrics. The accelerated coverage-guided fuzzing skipes redundant instructions to improve the testing efficiency. An efficient test set is built by fuzzing and the experimential results indicate that our method can maximize coverage metrics close to 100% in a short time, thereby ensuring a comprehensive and efficient coverage for processor testing. © 2024 IEEE.

关键词： Equivalence classes

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A Low-power and High-accuracy Accelerator with Voice Classification for keyword Spotting 16

A Low-power and High-accuracy Accelerator with Voice Classif...

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16th IEEE International Conference on Solid-state and Integrated Circuit Technology, ICSICT 2022

作者： Shao, Tianyu Han, Jun Fudan University State Key Laboratory of Asic and System Shanghai200433 China

ISBN: (数字)9781665469067

ISBN: (纸本)9781665469067

A design for low-power and high-accuracy keyword spotting (KWS) accelerator with voice classification module and reconfigurable processing element array is proposed in this paper. The accelerator extracts the MFCC features of input voice signals and classifies them into two types by GMM template matching. Each type of voice applies its specific network parameters for the keyword spotting. In addition, a reconfigurable acceleration module with a 3×12 PE array is designed. Four different operators among the DS-CRNN network can be mapped into the hardware structure to multiplex the hardware resources, and efficient data multiplexing can also be performed. Our KWS accelerator achieves the recognition accuracy of 92.0% with the power consumption of 50.4mW, providing possibility for embedded application of KWS system. © 2022 IEEE.

关键词： Template matching

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Hybrid Attention Spatial-Temporal Network for Video Saliency Prediction 16

Hybrid Attention Spatial-Temporal Network for Video Saliency...

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16th IEEE International Conference on Solid-state and Integrated Circuit Technology, ICSICT 2022

作者： Dong, Qi-Yun Chen, Geng-Sheng Zhou, Xiao-Fang Fudan University State Key Laboratory of Asic and System Shanghai201203 China

ISBN: (数字)9781665469067

ISBN: (纸本)9781665469067

Video saliency prediction (VSP) is to understand and model a human's visual attention in a dynamic scene. Current methods tend to generate visual representations on a fixed local spacetime, neglecting the inherent long-range spatiotemporal relations. To remedy this deficiency, in this paper, we propose a new Hybrid Attention Spatial-Temporal Network (HAST-Net) for VSP. First, we design a novel Local Perception Module (LPM) to combine a dynamic position encoding block and a channel attention block together for a more effective extraction of position relations and channel information. Second, we use a Spatial-Temporal Multi-head Self-attention (STMSA) module, followed by a Convolutional Residual Feed Forward Network (CRFFN) module, to capture the long-range spatiotemporal dependencies. Third, we add above modules to a 3D convolutional backbone, place them in sequence to integrate channel attention with self-attention. Experiment results show that our model outperforms the state-of-the-art models, increasing the NSS and CC on DHF1K dataset by 2.8% and 2.7% respectively. © 2022 IEEE.

关键词： Behavioral research

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