2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)最新文献_第3页

Deep Convolutional Neural Network (DCNN) for Skin Cancer Classification 深度卷积神经网络(DCNN)用于皮肤癌分类

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294814

N. Aburaed, A. Panthakkan, M. Al-Saad, S. Amin, W. Mansoor

引用次数: 15

An Efficient Register Renaming Technique with Delayed Allocation and Register Packing 具有延迟分配和寄存器打包的有效寄存器重命名技术

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294955

Xianhua Liu, Qinghong Yang, Miao Tao, Qinshu Chen, Xu Cheng

引用次数: 1

Nested Pipeline Hardware Self-Organizing Map for High Dimensional Vectors 高维向量的嵌套管道硬件自组织映射

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294973

H. Hikawa

引用次数: 1

Structure of a LIFI Dedicated Binary Pixel Array LIFI专用二进制像素阵列的结构

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294883

Yoann Seauve, M. Vigier, Thomas Pilloix, L. Maret, G. Sicard

引用次数: 0

High PSR output-capacitor-less LDO with double buffers technique 采用双缓冲技术的高PSR输出-无电容LDO

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294966

R. Li, Xin Zhang, Yanhan Zeng, Yihan Lin, Jingci Yang, Hongzhou Tan

引用次数: 1

Self-Amplifying Current-Mode Multiplier Design using a Multi-Memristor Crossbar Cell Structure 采用多忆阻交叉栅结构的自放大电流模式倍增器设计

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294797

Shengqi Yu, R. Shafik, Thanasin Bunnam, Kaiyun Chen, Alexandre Yakovlev

{"title":"Self-Amplifying Current-Mode Multiplier Design using a Multi-Memristor Crossbar Cell Structure","authors":"Shengqi Yu, R. Shafik, Thanasin Bunnam, Kaiyun Chen, Alexandre Yakovlev","doi":"10.1109/ICECS49266.2020.9294797","DOIUrl":"https://doi.org/10.1109/ICECS49266.2020.9294797","url":null,"abstract":"Multipliers play a major role in modern compute-intensive applications such as artificial intelligence (AI) and signal processing. However, the logic complexity of conventional multipliers is a significant challenge for energy and performance efficiency. This paper proposes a novel current-mode multiplier without additional carry propagation and amplification circuits. The basic functional block is a one-transistor-multi-memristor (1TxM) cell, corresponding to a partial product term. In this cell, the transistor enables or disables the term by switching it ON or OFF, and the memristor acts as the resistive memory unit that determines the state of the cell: either high (i.e. logic 0) or low (i.e. logic 1). The number of memristors in a single cell is suitably chosen to achieve the required amplification depending on the significance of the cell current paths. This sidesteps the need to have a separate current mirror circuit for each path. The parallel current paths are then analogously accumulated to a common path to define the output, avoiding the complex carry propagation steps in conventional multipliers. Using Cadence Virtuoso analogue design environment, we carried out extensive experiments to confirm the functional and parametric properties of the multiplier. The results shows that the proposed multiplier reduces 64% energy cost when compared with recently proposed transistor-memristor cell based approaches.","PeriodicalId":404022,"journal":{"name":"2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130996687","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

A Low Power and Smart Power Unit for Kinetic Self-Sustainable Wearable Devices 一种用于动态自我可持续可穿戴设备的低功耗智能电源单元

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294783

Philipp Mayer, M. Magno, L. Benini

{"title":"A Low Power and Smart Power Unit for Kinetic Self-Sustainable Wearable Devices","authors":"Philipp Mayer, M. Magno, L. Benini","doi":"10.1109/ICECS49266.2020.9294783","DOIUrl":"https://doi.org/10.1109/ICECS49266.2020.9294783","url":null,"abstract":"A novel trend to achieve long-lifetime or even self-sustainable wearable devices is to exploit energy harvesting from environmental or body energy. Their power management circuits need to be carefully designed to enable a small-size energy-efficient wearable system, supporting multiple power domains ranging from mW in an active mode to nW in sleep modes. This work presents a fully configurable smart power unit suitable for kinetic energy harvesting transducers, Kinetron MGS, enabling self-sustainability for wearable devices. The proposed power management circuit hosts a low power microcontroller to manage the energy harvesting, voltage conversion from batteries, and wake-up circuits to exit low power states automatically. The source and the load power points are decoupled with multiple DC-DC converters aiming to supply loads with adaptive voltage scaling and high reliability. Experimental results using commercial micro-kinetic generators show the flexibility and efficiency of this approach: the proposed power supply unit achieves a quiescent current of 57 nA and a maximum load current of 300 mA, delivered with a harvesting efficiency of 79 %. We evaluate the proposed system with commercial kinetic energy harvesting transducer generating 1.18 mW when worn on the ankle during walking.","PeriodicalId":404022,"journal":{"name":"2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130483766","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: 2

Live Demonstration: Prosthesis Control Using a Real-Time Retina Cell Network Simulator 现场演示:使用实时视网膜细胞网络模拟器的假体控制

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294920

Coen Arrow, J. Eshraghian, Hancong Wu, Seungbum Baek, H. Iu, K. Nazarpour

引用次数: 1

Mirror Full Adder SET Susceptibility on 7nm FinFET Technology 7nm FinFET技术的镜面全加法器SET磁化率

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294891

Rafael N. M. Oliveira, F. A. D. Silva, R. Reis, C. Meinhardt

引用次数: 1

High Input Impedance Capacitively-coupled Neural Amplifier and Its Boosting Principle 高输入阻抗电容耦合神经放大器及其升压原理

2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS) Pub Date : 2020-11-23 DOI: 10.1109/ICECS49266.2020.9294928

Erwin H. T. Shad, Kebria Naderi, M. Molinas

{"title":"High Input Impedance Capacitively-coupled Neural Amplifier and Its Boosting Principle","authors":"Erwin H. T. Shad, Kebria Naderi, M. Molinas","doi":"10.1109/ICECS49266.2020.9294928","DOIUrl":"https://doi.org/10.1109/ICECS49266.2020.9294928","url":null,"abstract":"This article proposes a technique for increasing the input impedance of conventional capacitively-coupled neural amplifiers based on careful examination of its analytical model. Following the precise derivation of the input impedance model, the effect of a negative capacitor is exploited as boosting principle to the input impedance of capacitively-coupled neural amplifiers. In order to implement this negative capacitor, some modifications were made to the conventional structure to make them suitable for capacitively-coupled neural amplifiers. The boosting factor which is calculated after these modifications exhibits frequency dependant parameters which offers further flexibility in the design and tuning. The proposed method to improve the input impedance is tested through simulation in a commercially available 0.18 µm CMOS technology. The robustness of the proposed structure is tested through Monte Carlo simulation in the presence of mismatch and process variation. Although the input impedance dropped with a factor of 2 during Monte Carlo simulations, the proposed method can still boost the input impedance by a factor of 100 at 100 Hz. While the proposed method might increase the area consumption, it maintains power efficiency property. When the proposed neural amplifier is compared to the state-of-the-art in terms of noise, power and input impedance, it shows relatively higher input impedance with negligible effect on input referred noise and power consumption which makes this structure suitable for low-power applications.","PeriodicalId":404022,"journal":{"name":"2020 27th IEEE International Conference on Electronics, Circuits and Systems (ICECS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126362699","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: 0