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Design of Modular Multiplier Based on Memristor 基于忆阻器的模块化乘法器设计
2019 IEEE International Workshop on Future Computing (IWOFC Pub Date : 2019-12-01 DOI: 10.1109/IWOFC48002.2019.9078443
Zitao Wei, Yongjia Wang, Xianyang Jiang
{"title":"Design of Modular Multiplier Based on Memristor","authors":"Zitao Wei, Yongjia Wang, Xianyang Jiang","doi":"10.1109/IWOFC48002.2019.9078443","DOIUrl":"https://doi.org/10.1109/IWOFC48002.2019.9078443","url":null,"abstract":"Memristor is the newest member of the four basic electronic components (resistor, capacitor, inductor, and memristor). Based on its simple structure, high-density integration, and low power consumption, it can be utilized in various ways; One of which, the most interesting method is to achieve complete logic operations in the circuit. However, no large-scale integrated circuit has been worked out based on such method due to serious signal degradation. To demonstrate this potential, material implication logic (IMP) is adopted to implement modular multiplier. Specifically, the circuit is carried out by integrating CMOS circuit and emulating the abstract memristor working process in CMOS logic. The multiplier is simulated and streamed into a Xilinx FPGA for successful verification.","PeriodicalId":266774,"journal":{"name":"2019 IEEE International Workshop on Future Computing (IWOFC","volume":"16 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123326122","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
A Real-time Online Aircraft Neural Network System 实时在线飞机神经网络系统
2019 IEEE International Workshop on Future Computing (IWOFC Pub Date : 2019-12-01 DOI: 10.1109/IWOFC48002.2019.9078469
Ying Zhang, Qian Zhao, Leiyan Tao, Jian Cao, Minfeng Wei, Xing Zhang
{"title":"A Real-time Online Aircraft Neural Network System","authors":"Ying Zhang, Qian Zhao, Leiyan Tao, Jian Cao, Minfeng Wei, Xing Zhang","doi":"10.1109/IWOFC48002.2019.9078469","DOIUrl":"https://doi.org/10.1109/IWOFC48002.2019.9078469","url":null,"abstract":"In order to meet the information processing requirements that large amount of heterogeneous input data are in the real-time flight process of aircraft, a neural network is proposed in this paper, including convolution fixed-point sliding IP core, pooling compression quantization IP core and fully connected compression fusion IP core. Heterogeneous sensor data of the aircraft as the input of the system; The recognized result serves as the output of the system. Convolution of sliding window IP core can quickly extract data features by eliminating redundant data sliding window; Pooling compression quantization IP core, using compression quantization technology, improves system execution efficiency; Fully connected compressed fusion IP core is compressed fusion after reduction and quantification, whose output meets the requirements of high reliability and low power consumption of the aircraft online intelligent integration design.","PeriodicalId":266774,"journal":{"name":"2019 IEEE International Workshop on Future Computing (IWOFC","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129499216","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
Oscillation neuron based on threshold switching characteristics of niobium oxide films 基于氧化铌膜阈值开关特性的振荡神经元
2019 IEEE International Workshop on Future Computing (IWOFC Pub Date : 2019-12-01 DOI: 10.1109/IWOFC48002.2019.9078440
Qingxi Duan, Zhaokun Jing, Ke Yang, Ru Huang, Yuchao Yang
{"title":"Oscillation neuron based on threshold switching characteristics of niobium oxide films","authors":"Qingxi Duan, Zhaokun Jing, Ke Yang, Ru Huang, Yuchao Yang","doi":"10.1109/IWOFC48002.2019.9078440","DOIUrl":"https://doi.org/10.1109/IWOFC48002.2019.9078440","url":null,"abstract":"Here we report threshold switching characteristics in niobium oxide films, which is in turn used to build an oscillation neuron. In particular, we show that strong correlation exists between the oxygen flow ratio during NbOx film deposition and the electrical properties of NbOx devices. The NbOx devices can show metallic, volatile threshold switching, and non-volatile resistive switching characteristics, depending on the oxygen flow ratio. The NbOx device with threshold switching can be used to form an oscillation neuron displaying three critical features: all-or-nothing oscillation, threshold-driven oscillation and input-modulated frequency response, which could be promising for applications as artificial neurons in hardware neural networks.","PeriodicalId":266774,"journal":{"name":"2019 IEEE International Workshop on Future Computing (IWOFC","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125786506","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
Spiking Continuous Attractor Neural Networks with Spike Frequency Adaptation for Anticipative Tracking 基于脉冲频率自适应的脉冲连续吸引子神经网络
2019 IEEE International Workshop on Future Computing (IWOFC Pub Date : 2019-12-01 DOI: 10.1109/IWOFC48002.2019.9078445
Liutao Yu, Tianhao Chu, Zhao Zhao, Yuanyuan Mi, Yuchao Yang, Si Wu
{"title":"Spiking Continuous Attractor Neural Networks with Spike Frequency Adaptation for Anticipative Tracking","authors":"Liutao Yu, Tianhao Chu, Zhao Zhao, Yuanyuan Mi, Yuchao Yang, Si Wu","doi":"10.1109/IWOFC48002.2019.9078445","DOIUrl":"https://doi.org/10.1109/IWOFC48002.2019.9078445","url":null,"abstract":"Continuous attractor neural network (CANN) is a canonical model for neural information representation and processing, which has been applied to describe the encoding of continuous features, such as orientation, head direction and spatial location in neural systems. Specifically, theoretical studies based on a firing-rate model have found that a CANN with negative feedback, such as spike frequency adaptation (SFA), has the capability of tracking a continuously moving stimulus anticipatively. In this study, facing the booming development of neuromorphic computing using spiking neural networks (SNNs), we built a spiking continuous attractor neural network (S-CANN) with SFA to implement anticipative tracking. Further, we simplified the model, in terms of connection weights, external inputs, and network size, to facilitate its implementation with neuromorphic hardware.","PeriodicalId":266774,"journal":{"name":"2019 IEEE International Workshop on Future Computing (IWOFC","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121740951","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
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