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A Quantized Kernel Least Mean Square Scheme with Entropy-Guided Learning for Intelligent Data Analysis 被引量:5
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作者 Xiong Luo Jing Deng +3 位作者 Ji Liu Weiping Wang Xiaojuan Ban Jenq-Haur Wang 《China Communications》 SCIE CSCD 2017年第7期127-136,共10页
Quantized kernel least mean square(QKLMS) algorithm is an effective nonlinear adaptive online learning algorithm with good performance in constraining the growth of network size through the use of quantization for inp... Quantized kernel least mean square(QKLMS) algorithm is an effective nonlinear adaptive online learning algorithm with good performance in constraining the growth of network size through the use of quantization for input space. It can serve as a powerful tool to perform complex computing for network service and application. With the purpose of compressing the input to further improve learning performance, this article proposes a novel QKLMS with entropy-guided learning, called EQ-KLMS. Under the consecutive square entropy learning framework, the basic idea of entropy-guided learning technique is to measure the uncertainty of the input vectors used for QKLMS, and delete those data with larger uncertainty, which are insignificant or easy to cause learning errors. Then, the dataset is compressed. Consequently, by using square entropy, the learning performance of proposed EQ-KLMS is improved with high precision and low computational cost. The proposed EQ-KLMS is validated using a weather-related dataset, and the results demonstrate the desirable performance of our scheme. 展开更多
关键词 quantized kernel least mean square (QKLMS) consecutive square entropy data analysis
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Fast and Stable Surface Feature Simulation for Particle-Based Fluids 被引量:2
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作者 Xiaokun Wang Yanrui Xu +1 位作者 Xiaojuan Ban Pengfei Ye 《Journal of Beijing Institute of Technology》 EI CAS 2019年第1期57-66,共10页
In order to efficiently and realistically capture microscopic features of fluid surface,a fast and stable surface feature simulation approach for particle-based fluids is presented in this paper.This method employs a ... In order to efficiently and realistically capture microscopic features of fluid surface,a fast and stable surface feature simulation approach for particle-based fluids is presented in this paper.This method employs a steady tension and adhesion model to construct surface features with the consideration of the adsorption effect of fluid to solid.Molecular cohesion and surface area minimization are appended for surface tension,and adhesion is added to better show the microscopic characteristics of fluid surface.Besides,the model is integrated to an implicit incompressible smoothed particle hydrodynamics(SPH)method to improve the efficiency and stability of simulation.The experimental results demonstrate that the method can better simulates surface features in a variety of scenarios stably and efficiently. 展开更多
关键词 virtual REALITY 3D visualization FLUID simulation surface FEATURE
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Continuous Clustering Trajectory Stream of Moving Objects
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作者 于彦伟 王沁 王小东 《China Communications》 SCIE CSCD 2013年第9期120-129,共10页
The clustering of trajectories over huge volumes of streaming data has been rec- ognized as critical for many modem applica- tions. In this work, we propose a continuous clustering of trajectories of moving objects ov... The clustering of trajectories over huge volumes of streaming data has been rec- ognized as critical for many modem applica- tions. In this work, we propose a continuous clustering of trajectories of moving objects over high speed data streams, which updates online trajectory clusters on basis of incremental line- segment clustering. The proposed clustering algorithm obtains trajectory clusters efficiently and stores all closed trajectory clusters in a bi- tree index with efficient search capability. Next, we present two query processing methods by utilising three proposed pruning strategies to fast handle two continuous spatio-temporal queries, threshold-based trajectory clustering queries and threshold-based trajectory outlier detections. Finally, the comprehensive experi- mental studies demonstrate that our algorithm achieves excellent effectiveness and high effi- ciency for continuous clustering on both syn- thetic and real streaming data, and the propo- sed query processing methods utilise average 90% less time than the naive query methods. 展开更多
关键词 trajectory clustering moving obj-ect continuous query trajectory cluster trajec-tory outlier
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Dynamic Power Dissipation Control Method for Real-Time Processors Based on Hardware Multithreading
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作者 罗新强 齐悦 +1 位作者 王磊 王沁 《China Communications》 SCIE CSCD 2013年第5期156-166,共11页
In order to eliminate the energy waste caused by the traditional static hardware multithreaded processor used in real-time embedded system working in the low workload situation, the energy efficiency of the hardware m... In order to eliminate the energy waste caused by the traditional static hardware multithreaded processor used in real-time embedded system working in the low workload situation, the energy efficiency of the hardware multithread is discussed and a novel dynamic multithreaded architecture is proposed. The proposed architecture saves the energy wasted by removing idle threads without manipulation on the original architecture, fulfills a seamless switching mechanism which protects active threads and avoids pipeline stall during power mode switching. The report of an implemented dynamic multithreaded processor with 45 nm process from synthesis tool indicates that the area of dynamic multithreaded architecture is only 2.27% higher than the static one in achieving dynamic power dissipation, and consumes 1.3% more power in the same peak performance. 展开更多
关键词 dynamic power dissipation control real-time processor hardware multithread low power design energy efficiency
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Dynamic Time Division Multiple Access Algorithm for Industrial Wireless Hierarchical Sensor Networks
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作者 杨彦红 张晓彤 +1 位作者 罗琼 李文超 《China Communications》 SCIE CSCD 2013年第5期137-145,共9页
Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confli... Industrial wireless sensor networks adopt a hierarchical structure with large numbers of sensors and routers. Time Division Multiple Access (TDMA) is regarded as an efficient method to reduce the probability of confliction. In the intra-cluster part, the random color selection method is effective in reducing the retry times in an application. In the inter-cluster part, a quick assign algorithm and a dynamic maximum link algorithm are proposed to meet the quick networking or minimum frame size requirements. In the simulation, the dynamic maximum link algorithm produces higher reductions in the frame length than the quick assign algorithm. When the number of routers is 140, the total number of time slots is reduced by 25%. However, the first algorithm needs more control messages, and the average difference in the number of control messages is 3 410. Consequently, the dynamic maximum link algorithm is utilized for adjusting the link schedule to the minimum delay with a relatively high throughput rate, and the quick assign algorithm is utilized for speeding up the networking process. 展开更多
关键词 TDMA wireless sensor network industrial wireless sensor network
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Emotional State Transition Model Based on Stimulus and Personality Characteristics 被引量:3
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作者 彭晓兰 解仑 +1 位作者 刘欣 王志良 《China Communications》 SCIE CSCD 2013年第6期146-155,共10页
In order to use mathematical methods to study how cognitive reappraisal strategies affect the output state of emotions,Gross's cognitive reappraisal strategy is transformed into a quantitative parameter which is p... In order to use mathematical methods to study how cognitive reappraisal strategies affect the output state of emotions,Gross's cognitive reappraisal strategy is transformed into a quantitative parameter which is proposed to describe the general perception of emotional events on the basis of the emotion regulation.According to Gross's emotional regulation model,the Finite State Machine(FSM) model is used for describing the process of emotional state transition and the Likert 5 grading scale is introduced to study the level of an individual's reappraisal according to the participant's self-evaluation.The experimental results verify that the algorithm can effectively describe the relationship between the reappraisal strategy,emotional events and an emotiongenerative process.There are multiple dimensions of a human's emotional state.Thus,in the field of human-computer interaction,further research requires the development of a specific algorithm which can be implemented by a computer for the emotion regulation process. 展开更多
关键词 emotion regulation REAPPRAISAL emotional events conversion matrix
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A Novel Hidden Danger Prediction Method in CloudBased Intelligent Industrial Production Management Using Timeliness Managing Extreme Learning Machine
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作者 Xiong Luo Xiaona Yang +3 位作者 Weiping Wang Xiaohui Chang Xinyan Wang Zhigang Zhao 《China Communications》 SCIE CSCD 2016年第7期74-82,共9页
To prevent possible accidents,the study of data-driven analytics to predict hidden dangers in cloud service-based intelligent industrial production management has been the subject of increasing interest recently.A mac... To prevent possible accidents,the study of data-driven analytics to predict hidden dangers in cloud service-based intelligent industrial production management has been the subject of increasing interest recently.A machine learning algorithm that uses timeliness managing extreme learning machine is utilized in this article to achieve the above prediction.Compared with traditional learning algorithms,extreme learning machine(ELM) exhibits high performance because of its unique feature of a high generalization capability at a fast learning speed.Timeliness managing ELM is proposed by incorporating timeliness management scheme into ELM.When using the timeliness managing ELM scheme to predict hidden dangers,newly incremental data could be added prior to the historical data to maximize the contribution of the newly incremental training data,because the incremental data may be able to contribute reasonable weights to represent the current production situation according to practical analysis of accidents in some industrial productions.Experimental results from a coal mine show that the use of timeliness managing ELM can improve the prediction accuracy of hidden dangers with better stability compared with other similar machine learning methods. 展开更多
关键词 prediction incremental learning extreme learning machine cloud service
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