检索结果-内蒙古大学图书馆

2nd IEEE International Conference on Data science in Cyberspace, DSC 2017

作者： Zhu, Jiang Wu, Lingda Hao, Hongxing Song, Xiaorui Lu, Yi Science and Technology on Complex Electronic System Simulation Laboratory Equipment Academy Beijing China

ISBN: (纸本)9781538615997

The classification and visualization for surface objects receives a great deal of attention for high spectral dimensional data processing. A lot of methods were proposed and applied in this problem over the past decade. Whereas most of them still exist some challenge issues, include pre-treatment fussily, features extraction simplify, larger data processing difficultly and classification inaccurately. To solve these problems, we propose a novel method bases on deep learning which combines maximum noise fraction (MNF) and multilayers auto-encoders. Thereinto, MNF is used to reduce the inherent spectral dimensionality of high spectral dimensional data;autoencoders and softmax logistic regression function are applied for extracting high-level features and visualizing types of objects. On the experiments, we compared with traditional linear SVM method by using a 200-bands AVIRIS dataset over Indian Pines and a 103-bands ROSIS dataset over Italy Pavia. The results indicate that the algorithm in paper statistically significantly improved the classification and visualization accuracies and efficiencies. © 2017 IEEE.

关键词： Visualization

来源：评论

学校读者我要写书评

暂无评论

Research of multi-Agent cognition and decision 17

Research of multi-Agent cognition and decision

引用

2017 International Conference on E-Commerce, E-Business and E-Government, ICEEG 2017

作者： Liu, Dong Yan, Xuefei Li, Xinming Wang, Shoubiao Science and Technology on Complex Electronic System Simulation Laboratory Equipment Academy Beijing China

ISBN: (纸本)9781450352482

Reinforcement Learning(RL) is the main cognition and decision method of Agent since its adaptation and exploration ability to the unknown environment, but it cannot ensure the convergence for the multi-Agent situation since the transition of the state space is not only influenced by the Agent itself but also influenced by the other Agent's action, so the other Agent's action has to be taken into account. In consideration of the deep theory foundation and advantages to deal with the other player's policy, this paper think that combination of the games theory and multi-Agent is a breakthrough for the cognition and decision in the status of the multi-Agent Learning. Based on the introduction of the traditional decision technology, the learning technology and the typical algorithm framework of the multi-Agent reinforcement learning with the games theory, some related algorithms such as MinMax-Q, nash-Q, FF-Q, CE-Q and Nego-Q were presented and analyzed. © 2017 Association for Computing Machinery.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Distributed Opportunistic Channel Access Under Single-Bit CSI Feedback 6th

Distributed Opportunistic Channel Access Under Single-Bit CS...

引用

6th EAI International Conference on IoT as a Service, IoTaaS 2020

作者： Wang, Tongtong Zhang, Zhou Guo, Jing Tianjin China Science and Technology on Complex Aviation System Simulation Laboratory Beijing China

ISBN: (纸本)9783030675134

In this research, the problem of distributed opportunistic channel access is investigated under single-bit channel state information (CSI) feedback in ad hoc networks. In finding an optimal strategy achieving the maximum average system throughput, the optimal stopping approach is used, and an optimal strategy is proposed. In it, each winner source decides when to take transmission opportunity based on singe-bit feedback information. Moreover, an optimal quantization vector is also derived for the strategy. Interestingly, it is pure-threshold based, and the optimal quantization vector is fixed. All thresholds can be calculated off-line, and easy implementation is available. Through simulation, the effectiveness and efficiency of the optimal strategy are also verified. © 2021, ICST Institute for Computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Vector quantization

来源：评论

学校读者我要写书评

暂无评论

Nanopowder production by gas-embedded electrical explosion of wire

引用

Chinese Physics B 2013年第4期22卷 350-353页

作者：邹晓兵毛志国王新新江伟华 State Key Laboratory of Control and Simulation of Power System and Generation Equipments Department of Electrical Engineering Tsinghua University Department of Physics and Chemistry College of Science North China University of Technology

A small electrical explosion of wire （EEW） setup for nanopowder production is constructed. It consists of a low inductance capacitor bank of 2 μF–4 μF typically charged to 8 kV–30 kV, a triggered gas switch, and a production chamber housing the exploding wire load and ambient gas. With the EEW device, nanosize powders of titanium oxides, titanium nitrides, copper oxides, and zinc oxides are successfully synthesized. The average particle size of synthesized powders under different experimental conditions is in a range of 20nm–80nm. The pressure of ambient gas or wire vapor can strongly affect the average particle size. The lower the pressure, the smaller the particle size is. For wire material with relatively high resistivity, such as titanium, whose deposited energy Wd is often less than sublimation energy W s due to the flashover breakdown along the wire prematurely ending the Joule heating process, the synthesized particle size of titanium oxides or titanium nitrides increases with overheat coefficient k （k = W d /Ws ） increasing.

关键词： electrical explosion of wire nanosized powders particle size

来源：评论

学校读者我要写书评

暂无评论

Research on weapon system portfolio selection based on combat network modeling 11

Research on weapon system portfolio selection based on comba...

引用

11th Annual IEEE International systems Conference, SysCon 2017

作者： Cheng, Cheng Li, Jichao Zhao, Qingsong Jiang, Jiang Yu, Lixin Shang, Huilin College of Information System and Management National University of Defense Technology Changsha China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9781509046225

Joint operations and combat system-of-systems encounter have become major developing trends of modern warfare. Weapon system portfolio selection attracts much attention, because it is closely related to the production, deployment and operation of weapons, which is a crucial factor determining the outcome of the war. This paper presents a portfolio selection model of the weapon systems based on the combat network. Firstly, we describe the portfolio selection problem of weapon systems based on the combat network, introduce the concept of operation loop, and analyze difficulties and strategies of the optimization problem. Then on this basis, the combat network of the weapon equipment system is modeled, and the operational capability evaluation index of weapon system-of-systems based on the operational loop is constructed. Portfolio selection model based on combat network is established to maximize the combined combat capability of the weapon as an optimization target, and the capacity demand and the expense restriction as constraints. Finally, we take the missile defense system as a example to demonstrate the whole calculation process and results of the weapon system portfolio selection based on the combat network model. It shows that our proposed method can achieve a very good performance to solve weapon system portfolio selection problems. © 2017 IEEE.

关键词： system of systems

来源：评论

学校读者我要写书评

暂无评论

Multiple Algorithms Against Multiple Hardware Architectures: Data-Driven Exploration on Deep Convolution Neural Network 16th

Multiple Algorithms Against Multiple Hardware Architectures:...

引用

16th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2019

作者： Xu, Chongyang Luan, Zhongzhi Gao, Lan Wang, Rui Zhang, Han Zhang, Lianyi Liu, Yi Qian, Depei Beihang University Beijing China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9783030307080

With the rapid development of deep learning (DL), various convolution neural network (CNN) models have been developed. Moreover, to execute different DL workloads efficiently, many accelerators have been proposed. To guide the design of both CNN models and hardware architectures for a high-performance inference system, we choose five types of CNN models and test them on six processors and measure three metrics. With our experiments, we get two observations and conduct two insights for the design of CNN algorithms and hardware architectures. © 2019, IFIP International Federation for Information Processing.

关键词： Neural network models

来源：评论

学校读者我要写书评

暂无评论

Towards optimized tensor code generation for deep learning on sunway many-core processor

引用

Frontiers of Computer science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

来源：评论

学校读者我要写书评

暂无评论

Lower bound for transient growth of inclined buoyancy layer

引用

Applied Mathematics and Mechanics(English Edition) 2017年第6期38卷 779-796页

作者： Xiangming XIONG Jianjun TAO Center for Applied Physics and Technology (CAPT)-MOE Key Laboratory of High Energy Density Physics Simulation (HEDPS) State Key Laboratory for Turbulence and Complex System (SKLTCS)Department of Mechanics and Engineering ScienceCollege ofEngineeringPeking University

The relationship between stabilities of the buoyancy boundary layers along an inclined plate and a vertical plate immersed in a stratified medium is studied theoretically and numerically. The eigenvalue problem of energy stability is solved with the method of descending exponentials. The disturbance energy is found to be able to grow to 11.62 times as large as the initial disturbance energy for Pr = 0.72 when the Grashof number is between the critical Grashof numbers of the energy stability and the linear stability. We prove that, with a weighted energy method, the basic flow of the vertical buoyancy boundary layer is stable to finite-amplitude streamwise-independent disturbances.

关键词： natural convection boundary layer energy method transient growth

来源：评论

学校读者我要写书评

暂无评论

Compression Strategy of Structured Text Based on Prior Dictionary for Data Distribution system 2

Compression Strategy of Structured Text Based on Prior Dicti...

引用

2nd International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2022

作者： Li, Kefei Jia, Yijiang Ji, Yunhui Xie, Baodi Zhang, Wei Lu, Ping Chen, Jincai Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan430074 China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing100854 China

ISBN: (纸本)9781510660571

Data distribution service (DDS) is a middleware API standard from Object Management Group (OMG), which transfers data using a publisher-subscriber model. The number of distributed nodes deployed in today's DDS communication system can reach tens of thousands, thus improving the efficiency of the communication system is important. In this work we present a structured text encoding strategy based on prior dictionary. This compression method has considerable compression effect on structured text such as HTML. In our evaluation, the average data compression rate is reduced by 7.07%, and the average system latency is reduced by 8.61% comparing to Zlib. © 2022 SPIE.

关键词： Middleware

来源：评论

学校读者我要写书评

暂无评论

Stable Periodic Frequent Itemset Mining on Uncertain Datasets 4

Stable Periodic Frequent Itemset Mining on Uncertain Dataset...

引用

4th IEEE International Conference on Computer and Communication Engineering technology, CCET 2021

作者： He, Ruimeng Chen, Jinchao Du, Chenglie Duan, Yuxin Northwestern Polytechnical University Department of Computer Science Xi'an China Science and Technology on System Simulation Laboratory Beijing Simulation Center Beijing China

ISBN: (纸本)9781665438902

In recent years, data mining has attracted great attention from the information industry. The main reason is that there is a large amount of data, which can be widely used, and there is an urgent need to convert these data into useful information and knowledge. Frequent itemset mining as an important research basis in data mining research has also been greatly developed. However, most of these frequent itemset mining algorithms only consider the frequency of itemsets and ignore the periodicity of itemsets, which makes the results incomplete. In order to solve the above problem, this paper presents a a stable periodic frequent itemset mining (SPFIM) algorithm on uncertain dataset, by considering both the frequency and periodicity of itemsets. The experimental evaluation on real datasets shows that the SPFIM algorithm is efficient and can find patterns that are not found by traditional algorithms. © 2021 IEEE.

关键词： Data mining

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：