检索结果-内蒙古大学图书馆

A fine acquisition algorithm based on fast three-time FRFT for dynamic and weak GNSS signals

Journal of systems Engineering and Electronics 2023年第2期34卷 259-269页

作者： PAN YI ZHANG Sheng WANG Xiao LIU Manhao LUO Yiran Key Laboratory of Advanced Sensor and Integrated System Shenzhen International Graduate SchoolTsinghua UniversityShenzhen 518055China Department of Aeronautical and Aviation Engineering Hong Kong Polytechnic UniversityHong Kong 999077China

As high-dynamics and weak-signal are of two primary concerns of navigation using Global Navigation Satellite system(GNSS)signals,an acquisition algorithm based on threetime fractional Fourier transform(FRFT)is presented to simplify the calculation ***,the correlation results similar to linear frequency modulated(LFM)signals are derived on the basis of the high dynamic GNSS signal ***,the principle of obtaining the optimum rotation angle is analyzed,which is measured by FRFT projection lengths with two selected rotation ***,Doppler shift,Doppler rate,and code phase are accurately estimated in a real-time and low signal to noise ratio(SNR)wireless communication *** theoretical analysis and simulation results show that the fast FRFT algorithm can accurately estimate the high dynamic parameters by converting the traditional two-dimensional search process to only three times *** the acquisition performance is basically the same,the computational complexity and running time are greatly reduced,which is more conductive to practical application.

关键词： Global Navigation Satellite system(GNSS)signal fractional Fourier transform(FRFT) acquisition high-dynamics weak-signal

来源：评论

学校读者我要写书评

暂无评论

A 32GHz Two-stage Frequency Synthesizer with 100MHz Reference using Injection Locked Technology 5

A 32GHz Two-stage Frequency Synthesizer with 100MHz Referenc...

引用

5th international Conference on Electronics and Communication, Network and Computer Technology, ECNCT 2023

作者： Li, Zhenhua Zhang, Sheng Tsinghua Shenzhen International Graduate School Key Laboratory of Advanced Sensor and Integrated System Shenzhen China

ISBN: (纸本)9798350328660

The article presents the design of a high-speed clock signal generation circuit which is capable of delivering high-speed clock signals at 8GHz and 32GHz. A two-stage architecture is used in the design to suppress in-band phase noise and improve the integral power efficiency respectively. In the first stage, a sub-sampling phase locked loop(SSPLL) with a dead-zone controlled frequency tracking loop is adopted to realize better frequency establishment and in-band phase noise performance. The second stage utilizes the intermediate signal and injection-locked voltage-controlled-oscillator(ILVCO) to achieve frequency multiplication in millimeter-wave frequency band. To guarantee the frequency selection characteristics of the LC tank and ease the ratio between the frequency of injected signals and the conduction time of differential injected transistors, two injection-locked frequency doublers with push-push topology are cascaded and four times frequency multiplication is presented. The frequency synthesizer is designed by TSMC 28nm CMOS process and achieves 70-fs jitter in the time domain with 42.6-mW power consumption at 32GHz and a figure of merit of-246.8dB. © 2023 IEEE.

关键词： Frequency synthesizers

来源：评论

学校读者我要写书评

暂无评论

A Wavelength-Multiplexed Photonic Tensor Processor based on Mach-Zehnder Modulator 3

A Wavelength-Multiplexed Photonic Tensor Processor based on ...

引用

3rd international Conference on Laser, Optics, and Optoelectronic Technology, LOPET 2023

作者： Li, Hongfei Lin, Zeyu Zhang, Sheng Key Laboratory of Advanced Sensor and Integrated System Tsinghua Shenzhen International Graduate School Shenzhen518055 China

ISBN: (纸本)9781510667624

Photonic processors have shown great potential to replace electronic processors due to the high parallelism, low latency, and low power consumption of light. The current direction of integrated optical computing research is focused on realizing vector matrix multiplication in light, which is also called photonic tensor processor. There are two main implementation schemes of photonic tensor processors: coherent and wavelength division multiplexing, and the latter is represented by the micro-ring resonator (MRR) weight bank. However, the MRR is highly sensitive to the manufacturing error, and it takes a long time to calibrate before used for calculation, which makes the realization of a large-scale MRR weight bank a challenge. We propose a novel architecture of wavelength-multiplexed photonic tensor processor based on Mach-Zehnder modulators (MZMs), which can reduce the time and power cost of device calibration We implement a 4×4 optical convolution operator based on the above architecture, which is used to solve the MNIST handwritten digit recognition problem. Prediction accuracy of 91.72% is achieved compared with the accuracy 97.58% achieved by a computer. © 2023 SPIE.

关键词： Tensors

来源：评论

学校读者我要写书评

暂无评论

Design and Analysis of Surge Protection Circuit in the Memory Architecture of FeRAM 8

Design and Analysis of Surge Protection Circuit in the Memor...

引用

8th international Conference on Electronic Technology and Information Science, ICETIS 2023

作者： Yang, Dongsen Zhang, Sheng Key Laboratory of Advanced Sensor and Integrated System Shenzhen Tsinghua Shenzhen International Graduate School Shenzhen518055 China

ISBN: (纸本)9781510666535

The frequent occurrences of surge current[1] of memory architecture in FeRAM, and the lack of necessary formula derivation in related researches of FeRAM are main aspects of what this work focuses. Therefore, the surge protection circuit is designed and simulated by this work with solid memory architecture of FeRAM to decrease the surge current and average power consumption creatively. The surge protection circuit is composed of a MOSFET and an RC delay circuit, which forces the generation of the surge current to be slowed down by mandatory precharge of the capacitor. On the other hand, necessary circuit analysis and formula derivation are concluded to predict the DC operating point of sensitive amplifier and build a clearly defined limits of operating voltage and the ratio of the maximum ferroelectric capacitance and bitline capacitance in the read/write operation of FeRAM. © 2023 SPIE.

关键词： Capacitance

来源：评论

学校读者我要写书评

暂无评论

MPICC: Multiple-Precision Inter-Combined MAC Unit with Stochastic Rounding for Ultra-Low-Precision Training 25

MPICC: Multiple-Precision Inter-Combined MAC Unit with Stoch...

引用

30th Asia and South Pacific Design Automation Conference, ASP-DAC 2025

作者： Huang, Leran Liu, Yongpan Lin, Xinyuan Wei, Chenhan Sun, Wenyu Wang, Zengwei Cao, Boran Zhang, Chi Fu, Xiaoxia Zhao, Wentao Zhang, Sheng Tsinghua Shenzhen International Graduate School Key Laboratory of Advanced Sensor and Integrated System Shenzhen China Tsinghua University Department of Electronic Engineering Beijing China

ISBN: (纸本)9798400706356

Recent studies have proved the feasibility of ultra-low-precision (≤ 8-bit) training. However, most of the existing operational circuits support only a few higher precisions (FP16, FP32, etc.) for multiplication, and the bit width for accumulation cannot be reduced, which results in low area and power efficiencies. In this paper, we propose MPICC, a multiple-precision Multiply-Accumulate (MAC) unit designed for ultra-low-precision training. It supports inter-combined computations across 18 different precision combinations, including LOG4 (radix-4 FP4), FP4, FP6, FP8, and INT4. It also reduces the accumulation precision from FP16 to FP12 through an optimized Stochastic Rounding (SR) strategy to further save logic resources. Moreover, a low-cost emulating controller, which time-division multiplexed the low-precision MAC unit, is also designed to accomplish high-precision computations for critical DNN layers. Compared with the existing multiple-precision computing units, the area/energy efficiencies of this design are improved by 1.17×/1.19× at FP8, and 4.69×/3.64× at FP4, respectively. The SR strategy further reduces the area/power consumption by 15.6%/14.9% of the floating-point accumulator. © 2025 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Cross-Layer Exploration and Chip Demonstration of In-sensor Computing for Large-Area Applications with Differential-Frame ROM-Based Compute-In-Memory 24

Cross-Layer Exploration and Chip Demonstration of In-Sensor ...

引用

61st ACM/IEEE Design Automation Conference, DAC 2024

作者： Liu, Jialong Tang, Wenjun Chen, Deyun Jiang, Chen Yang, Huazhong Li, Xueqing Department of Electronic Engineering BNRist Tsinghua University Beijing China Key Laboratory of Advanced Sensor and Integrated System Tsinghua Shenzhen International Graduate School China

ISBN: (纸本)9798400706011

In-sensor computing has emerged as a promising approach to mitigating huge data transmission costs between sensors and processing units. Recently, the emerging application scenarios have raised more demands of sensory technology for large-area and flexible integration. However, with thin-film technologies that are capable of providing flexible and large-area integration support, the implementation of in-sensor computing can be strongly restricted due to the low device performance, large-area integration variation, and costly interface between sensors and CMOS processors. To address this challenge, we propose an in-sensor computing architecture to facilitate high-parallelism NN pre-processing and effective data compression. The boundaries of computing parallelism are expanded by adopting compact ROM-based compute-in-memory scheme next to sensing array. Differential-frame computing provides not only excellent robustness, but also high data sparsity. A bio-inspired data compression method with residual recovery caches and zero-skip circuits further enhances output sparsity without accumulated error. Based on the proposed cross-layer design optimization, an LTPS TFT-based ROM CiM chip has been fabricated and experimentally measured. The system-level evaluation demonstrates 3.85× speedup and 5.10× energy efficiency improvement compared with traditional architecture with separated sensors and processors, outperforming existing in-sensor computing works in large-area thin-film technology scenarios. © 2024 Copyright held by the owner/author(s).

关键词： Thin film transistors

来源：评论

学校读者我要写书评

暂无评论

An Energy-Efficient Quantized Inference Framework For Electro-Photonic Computing system

An Energy-Efficient Quantized Inference Framework For Electr...

引用

2022 international Conference on Optical and Photonic Engineering, icOPEN 2022

作者： Lin, Zeyu Li, Hongfei Lei, Yaxiong Li, Sen Zhang, Sheng Key Laboratory of Advanced Sensor and Integrated System Shenzhen International Graduate school Tsinghua University Shenzhen518055 China Beijing SiPhonC Co. Ltd Beijing100083 China

ISBN: (纸本)9781510661905

Deep Learning is developing rapidly and has made breakthroughs in various fields. As a result, the number of parameters in deep neural networks(DNNs) is scaling about 5× rate of Moore's Law. To meet the computing power needs of DNNs, new computing architectures have been proposed, and the electro-photonic computing system is one of them. With the physical characteristics of photons, the electro-photonic computing system has demonstrated great potential in improving the efficiency of convolution calculation. However, there are still much spcace for improvement in the energy efficiency of the electro-photonic computing system. And the high energy consumption led by the high-precision analog-to-digital converters(ADCs) is an important factor hindering the energy efficiency. ADCs dominate about 50% energy consumption of the entire system, and they will increase exponentially with the precision. But if the low-precision ADCs are used directly, they will destroy the computing accuracy in the convolution calculation and reduce the inference performance of DNNs. In this paper, we propose an energy-efficient quantized inference framework for electro-photonic computing system to balance the energy consumption of ADCs and the DNNs inference performance, which includes a multi-scale quantization scheme based on per-slice granularity and width variable optical matrix. The proposed framework can reduce the energy consumption of the system by using low-precision ADCs, and ensure the inference performance of the DNNs at the same time. The experiments are carried out in MobileNet-v2, ResNet50 and Vgg16 respectively. The experimental results show that the proposed quantized inference framework can reduce the precision of ADCs by 7 bits and compared with using the low-precision ADCs directly, it improves the model accuracy of 40.5%, 70.2% and 65.4% respectively, which is close to the full precision model. © 2022 SPIE.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

A 32GHz Two-stage Frequency Synthesizer with 100MHz Reference using Injection Locked Technology

A 32GHz Two-stage Frequency Synthesizer with 100MHz Referenc...

引用

Electronics and Communication, Network and Computer Technology (ECNCT), international Conference on

作者： Zhenhua Li Sheng Zhang Key Laboratory of Advanced Sensor and Integrated System Tsinghua Shenzhen International Graduate School Shenzhen China

关键词：

来源：评论

学校读者我要写书评

暂无评论

Proton storage chemistry in aqueous zinc-organic batteries:A review

引用

InfoMat 2023年第2期5卷 45-65页

作者： Xianming Deng James Kumankuma Sarpong Guobin Zhang Jing Hao Xu Zhao Linyuan Li Hongfei Li Cuiping Han Baohua Li Shenzhen Key Laboratory of Power Battery Safety and Shenzhen Geim Graphene Center Tsinghua Shenzhen International Graduate SchoolTsinghua UniversityShenzhenPeople's Republic of China School of System Design and Intelligent Manufacturing Southern University of Science and TechnologyShenzhenGuangdongPeople's Republic of China Faculty of Materials Science and Energy Engineering Institute of Technology for Carbon NeutralityShenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenPeople's Republic of China Shenzhen Key Laboratory of Energy Materials for Carbon Neutrality Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhenPeople's Republic of China

Benefiting from the advantageous features of structural diversity and resource renewability,organic electroactive compounds are considered as attractive cathode materials for aqueous Zn-ion batteries(ZIBs).In this review,we discuss the recent developments of organic electrode materials for aqueous *** the proton(H^(+))storage chemistry in aqueous Zn-organic batteries has triggered an overwhelming literature surge in recent years,this topic remains ***,our review focuses on this significant issue and summarizes the reported electrochemical mechanisms,including pure Zn^(2+)intercalation,pure H^(+)storage,and H^(+)/Zn^(2+)***,the impact of H^(+)storage on the electrochemical performance of aqueous ZIBs is discussed *** the significance of H^(+)storage,we also highlight the relevant characterization methods ***,perspectives and directions on further understanding the charge storage mechanisms of organic materials are *** hope that this review will stimulate more attention on the H^(+)storage chemistry of organic electrode materials to advance our understanding and further its application.

关键词： aqueous zinc-ion batteries H^(+)/Zn^(2+)co-storage organic electrode materials proton storage chemistry

来源：评论

学校读者我要写书评

暂无评论

Sense4FL: Vehicular Crowdsensing Enhanced Federated Learning for Autonomous Driving

arXiv

引用

arXiv 2025年

作者： Ma, Yanan Hu, Senkang Fang, Zhengru Ji, Yun Deng, Yiqin Fang, Yuguang Hong Kong JC Lab of Smart City Department of Computer Science City University of Hong Kong Hong Kong Hong Kong Key Laboratory of Advanced Sensor and Integrated System Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China

To accommodate constantly changing road conditions, real-time model training is essential for autonomous driving (AD). Federated learning (FL) serves as a promising paradigm to enable autonomous vehicles to train models collaboratively with their onboard computing resources. However, existing vehicle selection schemes for FL all assume predetermined and location-independent vehicles’ datasets, neglecting the fact that vehicles collect training data along their routes, thereby resulting in suboptimal vehicle selection. To improve the perception quality in AD for a region, we propose Sense4FL, a vehicular crowdsensing-enhanced FL framework featuring trajectory-dependent vehicular training data collection. To this end, we first derive the convergence bound of FL by considering the impact of both vehicles’ uncertain trajectories and uploading probabilities, from which we discover that minimizing the training loss is equivalent to minimizing a weighted sum of local and global earth mover’s distance (EMD) between vehicles’ collected data distribution and global data distribution. Based on this observation, we formulate the trajectory-dependent vehicle selection and data collection problem for FL in AD. Given that the problem is NP-hard, we develop an efficient algorithm to find the solution with an approximation guarantee. Extensive simulation results have demonstrated the effectiveness of our approach in improving object detection performance compared with existing benchmarks. © 2025, CC BY.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：