检索结果-内蒙古大学图书馆

Midwest Symposium on Circuits and systems (MWSCAS)

作者： Heba Abunahla Yasmin Halawani Baker Mohammad Anas Alazzam System on Chip Center Electrical Engineering and Computer Science Department Khalifa University Abu Dhabi UAE System on Chip Center Mechanical Engineering Department Khalifa University Abu Dhabi UAE

ISBN: (数字)9781728180588

ISBN: (纸本)9781728180595

This paper presents a novel analog resistive random-access memory (RRAM), named NeuroMem, which consists of Au/GO/Au. The device's resistance can be tuned to any value within its R OFF to R ON range with high precision. The analog characteristic of NeuroMem mimics the memorization behavior of the brain, which makes it great asset for artificial neural network applications. In this work, NeuroMem-based crossbars are fabricated to hold the synaptic weights needed to perform Iris classification. The weight values are mapped to conductance states within NeuroMem R OFF to R ON range, and then written accurately on the actual devices. Unlike other RRAM-based hardware with limited conductance states, in this work no quantization is needed which enables efficient in memory-computing without scarifying accuracy. Furthermore, Neuromem device has been demonstrated in crossbars on flexible polymer substrate using standard photolithography process, which facilitates producing low cost flexible electronics. This work opens up great insights towards realizing RRAM-based computing at the edge.

关键词： Memristors Resistance Artificial intelligence Graphene Electrodes Switches Iris

来源：评论

学校读者我要写书评

暂无评论

Result Aggregation Algorithm Based on Upward-Merging of Inter-satellite Visibility

Result Aggregation Algorithm Based on Upward-Merging of Inte...

引用

International Conference on Measuring Technology and Mechatronics Automation, ICMTMA

作者： Siwei Zhong Qianqian Qi Xiangwei Chen Huilong Fan Xi Zhang School of Computer Science and Engineering Central South University Changsha China Network Resource Management and Trust Evaluation Key Laboratory of Hunan Changsha China Joint Laboratory of Space Information System Changsha China

In the satellite constellation network, the calculation results between neighboring satellite nodes are collected according to the state of inter-satellite computing nodes to aggregate and merge the intermediate results, thereby obtaining accurate and efficient results of the original calculation task. When aggregating the intermediate results, in addition to the constraints of the visible time window with the main star, the visibility between the various computing nodes is also constantly changing. In order to simplify the irregular space environment, a results upward-merging algorithm is proposed based on k-means, which arranges and reduces the dimensionality of each satellite computing node in a one-dimensional time axis according to the size of the time window of the master satellite. Then the intermediate results are upward merged according to the inter-satellite visibility on this time axis. The experimental results show that our proposed algorithm can improve the reliability of data transmission and reduce the time consumption of result aggregation. It can well overcome the high latency problem of space communication in the satellite environment.

关键词： Satellite constellations Satellites Mechatronics Space communications Aggregates Fitting Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Implementation of Full Spin-State Interferometer

引用

Chinese Physics Letters 2019年第5期36卷 7-11页

作者： Peng-Ju Tang Peng Peng Xiang-Yu Dong Xu-Zong Chen Xiao-Ji Zhou State Key Laboratory of Advanced Optical Communication System and Network School of Electronics Engineering and Computer SciencePeking UniversityBeijing 100871 Collaborative Innovation Center of Extreme Optics Shanxi UniversityTaiyuan 030006

Matter-wave interferometers with spin quantum states are attractive in quantum manipulation and precision measurements. Here, five spatial interference patterns corresponding to the full spin states are observed in each run of the experiment, by the combination of the Majorana transition according to the exponential modulation of the magnetic field pulse decline curve and radio frequency coupling among multiple magnetic *** to the realization of two Majorana transitions, the interference fringe for the magnetic field insensitive state also has a higher contrast. After spatially overlapping the full magnetic sub-state interference patterns dozens of times in consecutive experimental measurements, clear fringes are still observed, indicating the great stability of the relative phases of different components. This indicates the potential to achieve an interferometer with multiple spin clocks.

关键词： In Implementation of Full Spin-State Interferometer

来源：评论

学校读者我要写书评

暂无评论

Algorithms in Machine Learning Paradigms 1

引用

丛书名： Studies in Computational Intelligence

2020年

作者： Jyotsna Kumar Mandal Somnath Mukhopadhyay Paramartha Dutta Kousik Dasgupta

来源：评论

学校读者我要写书评

暂无评论

Individual risk profiling for portable devices using a neural network to process the cognitive reactions and the emotional responses to a multivariate situational risk assessment

arXiv

引用

arXiv 2021年

作者： Jumelle, Frederic So, Kelvin Deng, Didan Bright Nation Limited Smart-Space 3F Cyberport Hong Kong Neuromorphic Interactive System Laboratory Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

In this paper, we are presenting a novel method and system for neuropsychological performance testing that can establish a link between cognition and emotion. It comprises a portable device used to interact with a cloud service which stores user information under username and is logged into by the user through the portable device;the user information is directly captured through the device and is processed by artificial neural network;and this tridimensional information comprises user cognitive reactions, user emotional responses and user chronometrics. The multivariate situational risk assessment is used to evaluate the performance of the subject by capturing the 3 dimensions of each reaction to a series of 30 dichotomous questions describing various situations of daily life and challenging the user's knowledge, values, ethics, and principles. In industrial application, the timing of this assessment will depend on the user's need to obtain a service from a provider such as opening a bank account, getting a mortgage or an insurance policy, authenticating clearance at work or securing online payments. © 2021, CC BY-NC-SA.

关键词： Risk assessment

来源：评论

学校读者我要写书评

暂无评论

Functional neural network for decision processing, a racing network of programmable neurons with fuzzy logic where the target operating model relies on the network itself

arXiv

引用

arXiv 2021年

In this paper, we are introducing a novel model of artificial intelligence, the functional neural network for modeling of human decision-making processes. This neural network is composed of multiple artificial neurons racing in the network. Each of these neurons has a similar structure programmed independently by the users and composed of an intention wheel, a motor core and a sensory core representing the user itself and racing at a specific velocity. The mathematics of the neuron’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education and medicine including the opportunity to design an intelligent learning agent with application in business operations supervision. We believe that this functional neural network has a promising potential to transform the way we can compute decision-making and lead to a new generation of neuromorphic chips for seamless human-machine interactions. © 2021, CC BY-NC-SA.

关键词： Neurons

来源：评论

学校读者我要写书评

暂无评论

Group-wise inhibition based feature regularization for robust classification

arXiv

引用

arXiv 2021年

作者： Liu, Haozhe Wu, Haoqian Xie, Weicheng Liu, Feng Shen, Linlin 1Computer Vision Institute College of Computer Science and Software Engineering 2SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society 3National Engineering Laboratory for Big Data System Computing Technology 4Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen 518060 China

The convolutional neural network (CNN) is vulnerable to degraded images with even very small variations (e.g. corrupted and adversarial samples). One of the possible reasons is that CNN pays more attention to the most discriminative regions, but ignores the auxiliary features when learning, leading to the lack of feature diversity for final judgment. In our method, we propose to dynamically suppress significant activation values of CNN by group-wise inhibition, but not fixedly or randomly handle them when training. The feature maps with different activation distribution are then processed separately to take the feature independence into account. CNN is finally guided to learn richer discriminative features hierarchically for robust classification according to the proposed regularization. Our method is comprehensively evaluated under multiple settings, including classification against corruptions, adversarial attacks and low data regime. Extensive experimental results show that the proposed method can achieve significant improvements in terms of both robustness and generalization performances, when compared with the state-of-the-art methods. Code is available at https://***/LinusWu/TENET_Training. Copyright © 2021, The Authors. All rights reserved.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Super-resolution compressive spectral imaging via two-tone adaptive coding

引用

Photonics Research 2020年第6期8卷 395-411页

作者： CHANG XU TINGFA XU GE YAN XU MA YUHAN ZHANG XI WANG FENG ZHAO GONZALO R.ARCE Key Laboratory of Photoelectronic Imaging Technology and System School of Optics and PhotonicsBeijing Institute of TechnologyBeijing 100081China School of Computer Science and Information Security Guilin University of Electronic TechnologyGuilin 541004China Department of Electrical and Computer Engineering University of DelawareNewarkDelaware 19716USA

Coded apertures with random patterns are extensively used in compressive spectral imagers to sample the incident scene in the image *** samplings,however,are inadequate to capture the structural characteristics of the underlying signal due to the sparsity and structure nature of sensing matrices in spectral *** paper proposes a new approach for super-resolution compressive spectral imaging via adaptive *** this method,coded apertures are optimally designed based on a two-tone adaptive compressive sensing(CS)framework to improve the reconstruction resolution and accuracy of the hyperspectral imager.A liquid crystal tunable filter(LCTF)is used to scan the incident scene in the spectral domain to successively select different spectral *** output of the LCTF is modulated by the adaptive coded aperture patterns and then projected onto a lowresolution detector *** coded aperture patterns are implemented by a digital micromirror device(DMD)with higher resolution than that of the *** to the strong correlation across the spectra,the recovered images from previous spectral channels can be used as a priori information to design the adaptive coded apertures for sensing subsequent spectral *** particular,the coded apertures are constructed from the a priori spectral images via a two-tone hard thresholding operation that respectively extracts the structural characteristics of bright and dark regions in the underlying ***-resolution image reconstruction within a spectral channel can be recovered from a few snapshots of low-resolution *** no additional side information of the spectral scene is needed,the proposed method does not increase the system *** on the mutual-coherence criterion,the proposed adaptive CS framework is proved theoretically to promote the sensing efficiency of the spectral *** and experiments are provided to demonstrate and assess the proposed adaptive cod

关键词： resolution spectral image

来源：评论

学校读者我要写书评

暂无评论

Efficient and Non-Invasive Rice Moisture Quantification Using Coupled Lines Microwave Sensor Design

Efficient and Non-Invasive Rice Moisture Quantification Usin...

引用

International Conference on Information Technology (INCIT)

作者： Pratya Phanomupatum Ravee Phromloungsri Decha Wongpatsa Tiwat Pongthavornkamol Phatcharanat Saeng-On Somchat Sonasang Electronics Faculty of Industrial Technology Nakhon Phanom University Nakhon Phanom Thailand Computer and Communication Engineering Faculty of Technology Udon Thani Rajabhat University Udon Thani Thailand Faculty of Agriculture and Technology Nakhon Phanom University Nakhon Phanom Thailand Location and Automatic Identification System Research Team Location and Automatic NECTEC National Science and Technology Development Agency Pathum Thani Thailand Electrical Elements and Wireless Devices Unit (EEWDU) Faculty of Industrial Technology Nakhon Phanom University Nakhon Phanom Thailand

ISBN: (数字)9798350366303

ISBN: (纸本)9798350366310

This research presents the design, simulation, and experimental validation of a novel microwave sensor for noninvasive moisture measurement in rice. The sensor employs coupled microstrip lines fabricated on an FR4 substrate, designed to operate at a center frequency of 900 MHz with a quarter-wavelength configuration. The Advanced Design system software was utilized for the simulation, where key parameters such as S 21 and phase response were analyzed across a frequency range of 0.1 to 3 GHz. The sensor was fabricated and tested using a Vector Network Analyzer, where the moisture content in rice samples was varied incrementally, and the sensor’s performance was evaluated based on the changes in transmission characteristics. The results demonstrated the sensor’s potential for accurate moisture detection in rice, showcasing its feasibility as a noninvasive measurement technique in agricultural applications. This study contributes to the development of efficient, real-time moisture measurement technologies in the food processing industry.

关键词： Microwave measurement Sensitivity Moisture measurement Moisture Network analyzers Microwave sensors Vectors Real-time systems system software Substrates

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Neural Network Techniques for Automatic Software Vulnerability Detection

A Comparative Study of Neural Network Techniques for Automat...

引用

Theoretical Aspects of Software engineering (TASE)

作者： Gaigai Tang Lianxiao Meng Huiqiang Wang Shuangyin Ren Qiang Wang Lin Yang Weipeng Cao School of computer science and technology Harbin Engineering University Harbin China National Key Laboratory of Science and Technology on Information System Security Institute of System Engineering Chinese Academy of Military Science Beijing China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Software vulnerabilities are usually caused by design flaws or implementation errors, which could be exploited to cause damage to the security of the system. At present, the most commonly used method for detecting software vulnerabilities is static analysis. Most of the related technologies work based on rules or code similarity (source code level) and rely on manually defined vulnerability features. However, these rules and vulnerability features are difficult to be defined and designed accurately, which makes static analysis face many challenges in practical applications. To alleviate this problem, some researchers have proposed to use neural networks that have the ability of automatic feature extraction to improve the intelligence of detection. However, there are many types of neural networks, and different data preprocessing methods will have a significant impact on model performance. It is a great challenge for engineers and researchers to choose a proper neural network and data preprocessing method for a given problem. To solve this problem, we have conducted extensive experiments to test the performance of the two most typical neural networks (i.e., Bi-LSTM and RVFL) with the two most classical data preprocessing methods (i.e., the vector representation and the program symbolization methods) on software vulnerability detection problems and obtained a series of interesting research conclusions, which can provide valuable guidelines for researchers and engineers. Specifically, we found that 1) the training speed of RVFL is always faster than Bi-LSTM, but the prediction accuracy of Bi-LSTM model is higher than RVFL; 2) using doc2vec for vector representation can make the model have faster training speed and generalization ability than using word2vec; and 3) multi-level symbolization is helpful to improve the precision of neural network models.

关键词： Training Neural networks Data preprocessing Static analysis Predictive models Feature extraction Software

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：