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Application of Wavelet Analysis tointerference elimination for Geochemical Hydrocarbon Exploration

Journal of Earth Science 2000年第1期19卷 91-93页

作者： Zhang Liuping Ruan Tianjian Faculty of Earth Resources, China University of Geosciences, Wuhan 430074

interference in the data of geochemical hydrocarbon exploration is a large obstacle for anomaly recognition. The multiresolution analysis of wavelet analysis can extract the information at different scales so as to provide a powerful tool for information analysis and processing. Based on the analysis of the geometric nature of hydrocarbon anomalies and background, Mallat wavelet and symmetric border treatment are selected and data pre-processing (logarithm-normalization) is established. This approach provide good results in Shandong and Inner Mongolia, China. It is demonstrated that this approach overcome the disadvantage of backgound variation in the window (interference in window), used in moving average, frame filtering and spatial and scaling modeling methods.

关键词： geochemical exploration petroleum exploration interference elimination wavelet analysis data processing anomaly recognition.

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Multi-Agent Deep Reinforcement Learning for Cross-Layer Scheduling in Mobile Ad-Hoc Networks

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China Communications 2023年第8期20卷 78-88页

作者： Xinxing Zheng Yu Zhao Joohyun Lee Wei Chen Department of Electronic Engineering and Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China Department of Electrical and Electronic Engineering Hanyang UniversityAnsan 15588South Korea

Due to the fading characteristics of wireless channels and the burstiness of data traffic,how to deal with congestion in Ad-hoc networks with effective algorithms is still open and *** this paper,we focus on enabling congestion control to minimize network transmission delays through flexible power *** effectively solve the congestion problem,we propose a distributed cross-layer scheduling algorithm,which is empowered by graph-based multi-agent deep reinforcement *** transmit power is adaptively adjusted in real-time by our algorithm based only on local information(i.e.,channel state information and queue length)and local communication(i.e.,information exchanged with neighbors).Moreover,the training complexity of the algorithm is low due to the regional cooperation based on the graph attention *** the evaluation,we show that our algorithm can reduce the transmission delay of data flow under severe signal interference and drastically changing channel states,and demonstrate the adaptability and stability in different *** method is general and can be extended to various types of topologies.

关键词： Ad-hoc network cross-layer scheduling multi agent deep reinforcement learning interference elimination power control queue scheduling actorcritic methods markov decision process

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A novel nest-based scheduling method for mobile wireless body area networks

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Digital Communications and Networks 2020年第4期6卷 514-523页

作者： Zhijun Xie Guangyan Huang Roozbeh Zarei Zhenyan Ji Hongwu Ye Jing He Department of Information Science and Engineering Ningbo UniversityNingboChina School of Information Technology Deakin UniversityMelbourneAustralia Ningbo Institute of Materials Technology and Engineering Chinese Academy of SciencesNingboChina School of Software Engineering Beijing Jiaotong UniversityBeijingChina Zhejiang Fashion Institute of Technology NingboChina Institute of Information Technology Nanjing University of Finance and EconomicsJiangsuNanjingChina Swinburne Data Science Research Institute Swinburne University of TechnologyMelbourneAustralia

Wireless Body Area Networks(WBANs)comprise various sensors to monitor and collect various vital signals,such as blood pressure,pulse,heartbeat,body temperature,and blood sugar.A dense and mobile WBAN often suffers from interference,which causes serious problems,such as wasting energy and degrading *** reality,not all of the sensors in WBAN need to be active at the same ***,they can be divided into different groups so that each group works in turn to avoid *** this paper,a Nest-Based WBAN Scheduling(NBWS)algorithm is proposed to cluster sensors of the same types in a single or multiple WBANs into different groups to avoid ***,we borrow the graph coloring theory to schedule all groups to work using a Time Division for Multimodal Sensor(TDMS)group scheduling *** theoretical analysis and experimental results demonstrate that the proposed NBWS algorithm performs better in terms of frequency of collisions,transmission delay,system throughput,and energy consumption compared to the counterpart methods.

关键词： interference elimination Nest Sensors Scheduling Wireless body area networks Graph coloring theory

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