The Experts below are selected from a list of 11604 Experts worldwide ranked by ideXlab platform
Kai Wang - One of the best experts on this subject based on the ideXlab platform.
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periodic solutions permanence and global attractivity of a delayed impulsive prey predator system with Mutual Interference
Nonlinear Analysis-real World Applications, 2013Co-Authors: Kai Wang, Yanling ZhuAbstract:Abstract In this paper, by utilizing the continuation theorem and the comparison theorem, and constructing a suitable Lyapunov functional, a delayed prey–predator system with Mutual Interference and impulses is studied. Some sufficient conditions are established for the existence of positive periodic solutions, permanence and global attractivity of the system. The conditions obtained are related to the Interference constant m , delays and impulses. An example is given to show the feasibility of the results.
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permanence and global asymptotical stability of a predator prey model with Mutual Interference
Nonlinear Analysis-real World Applications, 2011Co-Authors: Kai WangAbstract:Abstract In this paper, a predator-prey system with Mutual Interference is studied. Some sufficient conditions are obtained for permanence and global asymptotical stability of the system by using the comparison theorem and constructing a suitable Lyapunov function. It is significant that the Mutual Interference m , in Theorem 4.1 , Theorem 4.2 , is allowed to be any real-valued number in interval (0, 1), which improves the corresponding results in Wang and Zhu (2008) [14] , Wang (2009) [13] , Lin and Chen (2009) [16] and Wang, Du and Liang (2010) [17] (where the Mutual constant m needs to be a rational number). Moreover, it solves the open problem posed by Lin in [16] .
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existence and global asymptotic stability of positive periodic solution for a predator prey system with Mutual Interference
Nonlinear Analysis-real World Applications, 2009Co-Authors: Kai WangAbstract:Abstract In this paper, a Predator–Prey system with Mutual Interference is studied. Some sufficient conditions are obtained for the existence and global asymptotic stability of positive periodic solution for the system by utilizing Mawhin’s coincidence degree theorem and constructing a suitable Lyapunov functional. It is interesting that our results depend on the Mutual Interference constant. Furthermore, an example is illustrated to verify the results by simulating.
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global attractivity of positive periodic solution for a volterra model
Applied Mathematics and Computation, 2008Co-Authors: Kai Wang, Yanling ZhuAbstract:Abstract In this paper, by utilizing Mawhin’s continuation theorem and constructing suitable Lyapunov functional, a Volterra model with Mutual Interference and Holling II type functional response is studied. Some sufficient conditions are obtained for the existence, uniqueness and global attractivity of positive periodic solution of the model. Furthermore, the conditions are related to the Interference constant m and an example is illustrated to verify the results by using Maple.
Yongwan Park - One of the best experts on this subject based on the ideXlab platform.
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investigation on the occurrence of Mutual Interference between pulsed terrestrial lidar scanners
IEEE Intelligent Vehicles Symposium, 2015Co-Authors: Gunzung Kim, Jeongsook Eom, Yongwan ParkAbstract:LIDAR scanners are essential components of intelligent vehicles capable of autonomous travel. Mutual Interference between LIDAR scanners has not been regarded as a problem yet. Mutual Interference was identified as a problem of increased importance because of the appearance of safety functions and the increasing rate of vehicles equipped with LIDAR scanner. This paper will show the probability that any LIDAR scanner is probably interfered Mutually by considering spatial and temporal overlaps. It will present three types of experiments and their results are showed, according to the arrangement of two LIDAR scanners.
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occurrence and characteristics of Mutual Interference between lidar scanners
Proceedings of SPIE, 2015Co-Authors: Gunzung Kim, Jeongsook Eom, Seonghyeon Park, Yongwan ParkAbstract:The LIDAR scanner is at the heart of object detection of the self-driving car. Mutual Interference between LIDAR scanners has not been regarded as a problem because the percentage of vehicles equipped with LIDAR scanners was very rare. With the growing number of autonomous vehicle equipped with LIDAR scanner operated close to each other at the same time, the LIDAR scanner may receive laser pulses from other LIDAR scanners. In this paper, three types of experiments and their results are shown, according to the arrangement of two LIDAR scanners. We will show the probability that any LIDAR scanner will interfere Mutually by considering spatial and temporal overlaps. It will present some typical Mutual Interference scenario and report an analysis of the Interference mechanism.
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An Experiment of Mutual Interference between Automotive LIDAR Scanners
Proceedings - 12th International Conference on Information Technology: New Generations ITNG 2015, 2015Co-Authors: Gunzung Kim, Jeongsook Eom, Yongwan ParkAbstract:LIDAR scanners are essential components of intelligent vehicles capable of autonomous travel. Mutual Interference between LIDAR scanners has not been regarded as a problem yet. Mutual Interference was identified as a problem of increased importance because of the appearance of safety functions and the increasing rate of vehicles equipped with LIDAR scanner. This paper will show the probability that any LIDAR scanner will interfere Mutually by considering spatial and temporal overlaps. It will present some generic Interference scenarios and report on the current status of the analysis of Interference mechanisms.
Xiqin Wang - One of the best experts on this subject based on the ideXlab platform.
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decentralized automotive radar spectrum allocation to avoid Mutual Interference using reinforcement learning
arXiv: Signal Processing, 2020Co-Authors: Pengfei Liu, Yimin Liu, Tianyao Huang, Xiqin WangAbstract:Nowadays, Mutual Interference among automotive radars has become a problem of wide concern. In this paper, a decentralized spectrum allocation approach is presented to avoid Mutual Interference among automotive radars. Although decentralized spectrum allocation has been extensively studied in cognitive radio sensor networks, two challenges are observed for automotive sensors using radar. First, the allocation approach should be dynamic as all radars are mounted on moving vehicles. Second, each radar does not communicate with the others so it has quite limited information. A machine learning technique, reinforcement learning, is utilized because it can learn a decision making policy in an unknown dynamic environment. As a single radar observation is incomplete, a long short-term memory recurrent network is used to aggregate radar observations through time so that each radar can learn to choose a frequency subband by combining both the present and past observations. Simulation experiments are conducted to compare the proposed approach with other common spectrum allocation methods such as the random and myopic policy, indicating that our approach outperforms the others.
Daniel W Bliss - One of the best experts on this subject based on the ideXlab platform.
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radchat spectrum sharing for automotive radar Interference mitigation
IEEE Transactions on Intelligent Transportation Systems, 2019Co-Authors: Canan Aydogdu, Nil Garcia, Henk Wymeersch, Musa Furkan Keskin, Daniel W BlissAbstract:In the automotive sector, both radars and wireless communication are susceptible to Interference. However, combining the radar and communication systems, i.e., radio frequency (RF) communications and sensing convergence, has the potential to mitigate Interference in both systems. This article analyses the Mutual Interference of spectrally coexistent frequency modulated continuous wave (FMCW) radar and communication systems in terms of occurrence probability and impact, and introduces RadChat, a distributed networking protocol for mitigation of Interference among FMCW based automotive radars, including self-Interference, using radar and communication cooperation. The results show that RadChat can significantly reduce radar Mutual Interference in single-hop vehicular networks in less than 80 ms.
Canan Aydogdu - One of the best experts on this subject based on the ideXlab platform.
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radchat spectrum sharing for automotive radar Interference mitigation
IEEE Transactions on Intelligent Transportation Systems, 2019Co-Authors: Canan Aydogdu, Nil Garcia, Henk Wymeersch, Musa Furkan Keskin, Daniel W BlissAbstract:In the automotive sector, both radars and wireless communication are susceptible to Interference. However, combining the radar and communication systems, i.e., radio frequency (RF) communications and sensing convergence, has the potential to mitigate Interference in both systems. This article analyses the Mutual Interference of spectrally coexistent frequency modulated continuous wave (FMCW) radar and communication systems in terms of occurrence probability and impact, and introduces RadChat, a distributed networking protocol for mitigation of Interference among FMCW based automotive radars, including self-Interference, using radar and communication cooperation. The results show that RadChat can significantly reduce radar Mutual Interference in single-hop vehicular networks in less than 80 ms.
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Radar Communications for Combating Mutual Interference of FMCW Radars
2019 IEEE Radar Conference (RadarConf), 2019Co-Authors: Canan Aydogdu, Nil Garcia, Lars Hammarstrand, Henk WymeerschAbstract:Commercial automotive radars used today are based on frequency modulated continuous wave signals due to the simple and robust detection method and good accuracy. However, the increase in both the number of radars deployed per vehicle and the number of such vehicles leads to Mutual Interference, cutting short future plans for autonomous driving and active safety functionality. We propose and analyze a radar communications (RadCom) approach to reduce this Mutual Interference while simultaneously offering communication functionality. We achieve this by frequency division multiplexing radar and communications, where communications is built on a decentralized carrier sense multiple access protocol and is used to adjust the timing of radar transmissions. Our simulation results indicate that radar Interference can be significantly reduced, at no cost in radar accuracy.