2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS)最新文献_第2页

Mixed-Signal Ionoacoustic Analog Front-End for Proton Range Verification with $24 mu mathrm{m}$ Precision at 0.8 Gy Bragg Peak Dose 混合信号离子声模拟前端在0.8 Gy Bragg峰值剂量下质子距离验证，精度为$24 mu math {m}$

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8965201

E. Vallicelli, A. Baschirotto, S. Lehrack, W. Assmann, K. Parodi, S. Viola, G. Riccobene, M. Matteis

{"title":"Mixed-Signal Ionoacoustic Analog Front-End for Proton Range Verification with $24 mu mathrm{m}$ Precision at 0.8 Gy Bragg Peak Dose","authors":"E. Vallicelli, A. Baschirotto, S. Lehrack, W. Assmann, K. Parodi, S. Viola, G. Riccobene, M. Matteis","doi":"10.1109/ICECS46596.2019.8965201","DOIUrl":"https://doi.org/10.1109/ICECS46596.2019.8965201","url":null,"abstract":"This paper investigates a promising experimental technique for proton beams range verification based on Time-of-Flight (ToF) measurements of the acoustic waves emitted by the fast energy deposition occurring at the end of the particle range. In the field of oncological hadron therapy, the ionoacoustic ranging technique promises better precision than Positron Emission Tomography (PET) and opens the possibility of real-time beam monitoring, thus increasing treatment efficacy. The proposed technique has already proven to provide sub-mm accuracy at sub-clinical energies and to rely on smart and smaller (and hence more efficient) electronics instrumentation w.r.t. PET. However, state-of-the-art experiments lacks dedicated analog and digital electronics and heavily rely on offline noise rejection algorithms to achieve sub-mm precision. In this scenario, this work presents a complete analog-digital front-end dedicated to ionoacoustic experiments that improves the signal-to-noise ratio of a traditional non-dedicated systems by 6 dB and thus increments the measurement precision for a given deposited dose. The proposed system has been validated by both behavioral simulations and experimental data taken at the Maier-Leibniz Laboratories, where using the presented system a clear acoustic signal of 5 Pa amplitude and 2.3 MHz frequency has been detected at 11 dB Signal-to-Noise-Ratio with a 19.5 MeV proton beam in a water phantom target. ToF measurements allowed to determine the Bragg Peak position with $24 mu mathrm{m}$ precision and $26 mu mathrm{m}$ accuracy w.r.t. Geant4 simulations while delivering a total Bragg Peak dose of 0.8 Gy.","PeriodicalId":209054,"journal":{"name":"2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116439880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

P2M: A 2MPixel CMOS Image Sensor for Soft X-Ray Detection P2M:用于软x射线检测的200万像素CMOS图像传感器

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964996

I. Sedgwick, F. Krivan, I. Shevyakov, M. Zimmer, H. Graafsma, G. Cautero, D. Giuressi, R. Menk, G. Pinaroli, L. Stebel, A. Greer, N. Guerrini, U. Pedersen, N. Tartoni, S. Rah, H. Hyun, K. Kim, S. H. Kim, B. Boitrelle, F. Orsini, B. Marsh, T. Nicholls, A. Marras, C. Wunderer, J. Correa, S. Lange, M. Kuhn

引用次数: 0

Low power $380 mu mathrm{W}$ Energy Efficient 1.8 GHz Digitally Controlled Oscillator for IoT Applications 低功耗$380 mu mathm {W}$节能1.8 GHz数字控制振荡器，用于物联网应用

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964984

M. Moreira, L. Ferreira, Bárbara Souza, S. Ferreira, F. D. Baumgratz, S. Bampi

引用次数: 0

A Compact Industrial-Grade Multi-Threshold Brown-Out Detector 紧凑型工业级多阈值停电检测器

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964634

G. LuisE.Rueda, B. JuanSebastianMoya, E. Roa

引用次数: 1

Low-Cost Microwave Noise Source Exploiting a BJT with Junctions in Avalanche Regime 雪崩状态下带结的BJT低成本微波噪声源

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964981

G. Simoncini, F. Alimenti

引用次数: 0

Efficient NB-IoT and GNSS chipset solution 高效的NB-IoT和GNSS芯片组解决方案

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8965122

Woo-Hyoung Choi, Ivan Galkin, Seokwon Lee, Jihoon Park, Jongjin Lee, Dongyun Kim

引用次数: 1

Defect-Tolerant Crossbar Training of Memristor Ternary Neural Networks 忆阻器三元神经网络的容错横条训练

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964896

K. Pham, T. Nguyen, K. Min

{"title":"Defect-Tolerant Crossbar Training of Memristor Ternary Neural Networks","authors":"K. Pham, T. Nguyen, K. Min","doi":"10.1109/ICECS46596.2019.8964896","DOIUrl":"https://doi.org/10.1109/ICECS46596.2019.8964896","url":null,"abstract":"A memristor Ternary Neural Network (TNN) is a promising candidate for implementing neural networks for Internet-of-Things (IoT) applications, where low power and simple hardware are important. One important concern in the memristor TNN is that the real memristor crossbar has various defects such as stuck-at-faults, memristance variation, etc., like human brain's biological neurons and synapses. To mitigate the inference loss due to the memristive defects, we need to retrain the defective crossbar. However, the crossbar's retraining needs a long time and a large amount of energy of programming, because the memristors should be programmed one by one using Incremental Step Pulse Programming (ISPP) of flash memories. Here, we combine the partial-gated training scheme with the asymmetrical training for not only minimizing the recognition rate loss, but also saving the crossbar's programming time and energy. The CF scheme with 10% retraining indicates the programming energy can be saved by as large as ∼98%, in sacrifice with the MNIST rate loss of ∼0.6%, compared to the FF scheme with 100% retraining. The simulation indicates that the CF with 10% retraining will be useful for realizing the crossbar-based neural-network in large scale for future IoT applications.","PeriodicalId":209054,"journal":{"name":"2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126978195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Stochastic-Computing Based Brainwave LSI Towards an Intelligence Edge 基于随机计算的脑波LSI迈向智能边缘

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964739

N. Onizawa, W. Gross, T. Hanyu

引用次数: 0

A Memristor-CMOS Braun Multiplier Array for Arithmetic Pipelining 用于算术流水线的忆阻器- cmos布朗乘法器阵列

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964710

Seungbum Baek, J. Eshraghian, Sang-Hyun Ahn, A. P. James, Kyoungrok Cho

{"title":"A Memristor-CMOS Braun Multiplier Array for Arithmetic Pipelining","authors":"Seungbum Baek, J. Eshraghian, Sang-Hyun Ahn, A. P. James, Kyoungrok Cho","doi":"10.1109/ICECS46596.2019.8964710","DOIUrl":"https://doi.org/10.1109/ICECS46596.2019.8964710","url":null,"abstract":"A multiplier is a core building block in most digital signal and image processing systems and increasingly so in neural processing units. The latter must parallelize very large scale multiply-and-accumulate operations in deep learning with reconfigurable weights to be multiplied with varying input. In light of this, we propose a memristor-CMOS hybrid multiplier which uses a Braun structure to enable segmentation of the multiplier array to process various multiplication operations simultaneously with reconfigurable bit-widths by varying a control signal, all on the same multiplier. This enables an increase in computational throughput. Memristors are used as basic logic elements and improve area utilization by fabricating them in the back end of the line before the pad level. The CMOS chip is fabricated in the SK Hynix 180-nm process with TiO2 memristors separately deposited on top. A performance evaluation is undertaken under a 4-point Fast Fourier Transform, demonstrating a decrease in area by 17% and power consumption by 35%-49% with a 100MHz system clock when compared to similarly behaving CMOS multipliers.","PeriodicalId":209054,"journal":{"name":"2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","volume":"265 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120888322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Low-Noise Wide-Frequency Tunable Amplifier for Bioimpedance Spectroscopy Applications 生物阻抗光谱应用的低噪声宽频可调放大器

2019 26th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2019-11-01 DOI: 10.1109/ICECS46596.2019.8964905

A. Márquez, N. Medrano, B. Calvo

引用次数: 1