Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435899
Dongqing Liu, Weiwei Sun, Shuqing Wang
This paper proposes new results on fixed-time fuzzy control for a class of Hamiltonian systems based on event-triggered scheme. A fuzzy system is utilized to approximate an unknown function in the considered Hamiltonian system. In terms of fixed-time stability criterions, a novel controller is presented to stabilize the resulting closed-loop system in fixed-time on a neighborhood of the origin. Moreover, in order to save resources, an event-triggered scheme is established to update the controller according to the trigger conditions. Taking advantage of Lyapunov stability theory, some sufficient conditions are presented to make the system states converge to the origin in a fixed time. At the same time, under the designed controller, there exists a positive lower bound between adjacent trigger times, which means that the Zeno phenomenon is avoided in the proposed event-triggered mechanism. The validity of the designed controller and event-triggered approach is also verified by a circuit system simulation example.
{"title":"Fixed-Time Fuzzy Control for Hamiltonian Systems via Event-Triggered Approach","authors":"Dongqing Liu, Weiwei Sun, Shuqing Wang","doi":"10.1109/ICACI52617.2021.9435899","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435899","url":null,"abstract":"This paper proposes new results on fixed-time fuzzy control for a class of Hamiltonian systems based on event-triggered scheme. A fuzzy system is utilized to approximate an unknown function in the considered Hamiltonian system. In terms of fixed-time stability criterions, a novel controller is presented to stabilize the resulting closed-loop system in fixed-time on a neighborhood of the origin. Moreover, in order to save resources, an event-triggered scheme is established to update the controller according to the trigger conditions. Taking advantage of Lyapunov stability theory, some sufficient conditions are presented to make the system states converge to the origin in a fixed time. At the same time, under the designed controller, there exists a positive lower bound between adjacent trigger times, which means that the Zeno phenomenon is avoided in the proposed event-triggered mechanism. The validity of the designed controller and event-triggered approach is also verified by a circuit system simulation example.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124252781","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435863
Jintao Huang, X. Liao, Nankun Mu, Yunhang Zhu
In this paper, we investigate the limit cycle of a single-neuron system and its circuit design. By transforming the system into Lienard-type and using Poincaré-Bendixson theorem as well as the symmetry of this systems, we obtain the existence conditions of limit cycle of the system. Then, by comparing the integral value of the differential of positive definite function along two assumed limit cycles, we prove that the system cannot produce two coexisting limit cycles, which means that the system has at most one limit cycle. In addition, we give the numerical simulation, and realize the circuit design of the single-neuron system by using Multisim. The waveform diagram and phase diagram of the numerical simulation and circuit simulation are obtained respectively. By comparing the results of numerical and circuit simulation, the effectiveness of our mathematical analysis and the feasibility of circuit design are better illustrated.
{"title":"Limit Cycle of a Single-Neuron System and Its Circuitry Design","authors":"Jintao Huang, X. Liao, Nankun Mu, Yunhang Zhu","doi":"10.1109/ICACI52617.2021.9435863","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435863","url":null,"abstract":"In this paper, we investigate the limit cycle of a single-neuron system and its circuit design. By transforming the system into Lienard-type and using Poincaré-Bendixson theorem as well as the symmetry of this systems, we obtain the existence conditions of limit cycle of the system. Then, by comparing the integral value of the differential of positive definite function along two assumed limit cycles, we prove that the system cannot produce two coexisting limit cycles, which means that the system has at most one limit cycle. In addition, we give the numerical simulation, and realize the circuit design of the single-neuron system by using Multisim. The waveform diagram and phase diagram of the numerical simulation and circuit simulation are obtained respectively. By comparing the results of numerical and circuit simulation, the effectiveness of our mathematical analysis and the feasibility of circuit design are better illustrated.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120882499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435900
Le Wang, Jing Wu, Wei Sun
This paper considers the problem of event-triggered adaptive fuzzy control for a class of uncertain nonlinear systems. An adaptive event-triggered controller is designed by using the command filter techniques and backstepping method of fuzzy logic systems (FLS). In this design, the use of command filter technique solves the problem of the explosion of complexity in traditional backstepping approach. The proposed event-triggered adaptive fuzzy controller ensures that all signals in the closed-loop systems are bounded and saves network communication resources. Finally, the effectiveness of the proposed control strategy is proved by giving the simulation results.
{"title":"Adaptive Event-triggered Control for Uncertain Nonlinear Systems based Command Filtering","authors":"Le Wang, Jing Wu, Wei Sun","doi":"10.1109/ICACI52617.2021.9435900","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435900","url":null,"abstract":"This paper considers the problem of event-triggered adaptive fuzzy control for a class of uncertain nonlinear systems. An adaptive event-triggered controller is designed by using the command filter techniques and backstepping method of fuzzy logic systems (FLS). In this design, the use of command filter technique solves the problem of the explosion of complexity in traditional backstepping approach. The proposed event-triggered adaptive fuzzy controller ensures that all signals in the closed-loop systems are bounded and saves network communication resources. Finally, the effectiveness of the proposed control strategy is proved by giving the simulation results.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116577989","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435884
Shanshan Lu, Xiao Zhang, Yu Zhou, Shilong Sun
In recent years, unmanned aerial vehicles (UAVs) have been widely used as flying-based stations to provide wireless coverage services to ground users. Owing to the UAV’s limited battery capacity and coverage range, its energy consumption or coverage have been explored by researchers. However, the existing research largely overlooks the tradeoff involved in optimizing UAV swarm deployment for wireless coverage over a ground area. This study considers homogeneous UAV deployment in a 3D space to provide sustainable wireless services as a multi-objective problem. We introduce three objectives: 1) minimize the total energy consumption while deploying a UAV to UAVs on duty, 2) minimize the number of UAVs, and 3) maximize the coverage rate of the target area. With the aim of achieving a better trade-off between these objectives, we adopt the framework of MOEA/D, which allows search progress cooperating with neighboring subproblems each other. Particularly, we introduce a single-tuple encoding scheme and genetic operators (i.e., selection, crossover, and mutation) to generate feasible optimal solutions. The simulations demonstrate that the proposed algorithm is effective and surpasses the improved SPEA II and NSGA II, which indicates that the approach is dependable in solving the proposed multi-objective optimization for UAV deployment.
{"title":"MOEA/D based UAV swarm deployment for wireless coverage","authors":"Shanshan Lu, Xiao Zhang, Yu Zhou, Shilong Sun","doi":"10.1109/ICACI52617.2021.9435884","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435884","url":null,"abstract":"In recent years, unmanned aerial vehicles (UAVs) have been widely used as flying-based stations to provide wireless coverage services to ground users. Owing to the UAV’s limited battery capacity and coverage range, its energy consumption or coverage have been explored by researchers. However, the existing research largely overlooks the tradeoff involved in optimizing UAV swarm deployment for wireless coverage over a ground area. This study considers homogeneous UAV deployment in a 3D space to provide sustainable wireless services as a multi-objective problem. We introduce three objectives: 1) minimize the total energy consumption while deploying a UAV to UAVs on duty, 2) minimize the number of UAVs, and 3) maximize the coverage rate of the target area. With the aim of achieving a better trade-off between these objectives, we adopt the framework of MOEA/D, which allows search progress cooperating with neighboring subproblems each other. Particularly, we introduce a single-tuple encoding scheme and genetic operators (i.e., selection, crossover, and mutation) to generate feasible optimal solutions. The simulations demonstrate that the proposed algorithm is effective and surpasses the improved SPEA II and NSGA II, which indicates that the approach is dependable in solving the proposed multi-objective optimization for UAV deployment.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116262619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435882
Yang Li, Donghong Qin, Jinbo Zhang
Compared with traditional speech synthesis systems, end-to-end speech synthesis systems based on deep learning (such as DeepVoice3, Tacotron2) not only reduce the requirements for linguistic knowledge, but the synthesis effect is almost close to the level of human pronunciation. However, the end-to-end speech synthesis system based on deep learning has disadvantages such as missing words, repeated pronunciation, and slow synthesis speed. In view of the local information preference of the Tacotron2 model in the decoder, this paper proposes to maximize the interactive information between the text and the predicted acoustic features and use the WaveGlow synthesizer to reduce the local information preference and the problem of slow synthesis speed, pronunciation in the Tacotron2 model. Experimental results show that the improved model subjective evaluation MOS (Mean Opinion Score) score is 3.94, and the synthesis speed is significantly improved.
{"title":"Speech Synthesis Method Based on Tacotron2","authors":"Yang Li, Donghong Qin, Jinbo Zhang","doi":"10.1109/ICACI52617.2021.9435882","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435882","url":null,"abstract":"Compared with traditional speech synthesis systems, end-to-end speech synthesis systems based on deep learning (such as DeepVoice3, Tacotron2) not only reduce the requirements for linguistic knowledge, but the synthesis effect is almost close to the level of human pronunciation. However, the end-to-end speech synthesis system based on deep learning has disadvantages such as missing words, repeated pronunciation, and slow synthesis speed. In view of the local information preference of the Tacotron2 model in the decoder, this paper proposes to maximize the interactive information between the text and the predicted acoustic features and use the WaveGlow synthesizer to reduce the local information preference and the problem of slow synthesis speed, pronunciation in the Tacotron2 model. Experimental results show that the improved model subjective evaluation MOS (Mean Opinion Score) score is 3.94, and the synthesis speed is significantly improved.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128200289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435869
Ruitong Wu, Kunting Yu, Yong-ming Li
This paper investigates the problem of adaptive fuzzy 1-bit event-triggered control for stochastic nonlinear systems. In our design, we only need to transmit a 1-bit signal (either 1 or 0), whenever the triggering signal is updated. That is, the signal is transmitted between the controller and the actuator in the communication channel. With our proposed control scheme, which can further alleviate the communication burden. Based on the Lyapunov stability analysis, all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Meanwhile, Zeno behavior can be avoided.
{"title":"Adaptive Fuzzy 1-Bit Event-Triggered Control for Stochastic Nonlinear Systems","authors":"Ruitong Wu, Kunting Yu, Yong-ming Li","doi":"10.1109/ICACI52617.2021.9435869","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435869","url":null,"abstract":"This paper investigates the problem of adaptive fuzzy 1-bit event-triggered control for stochastic nonlinear systems. In our design, we only need to transmit a 1-bit signal (either 1 or 0), whenever the triggering signal is updated. That is, the signal is transmitted between the controller and the actuator in the communication channel. With our proposed control scheme, which can further alleviate the communication burden. Based on the Lyapunov stability analysis, all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Meanwhile, Zeno behavior can be avoided.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132191079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435866
Empilo Eynthon Guillaume Nelson, Songtao Guo
Considered as the key application of mobile edge computing (MEC), computation offloading emerges as a technology necessary to offload data for computation at an edge cloud. MEC is evolving as a promising technique susceptible to support resource constraint devices and delay sensitive applications, by delivering computing services nearby mobile users. Nevertheless, many studies have shown that latency remains one of the major challenges in MEC networks. However, in this paper, we propose to solve the latency challenge in mobile edge computing by developing the channel allocation-based demand assignment protocol for computation offloading (DAP-CO), and to tackle the server selection problem in a multi-edge server network so that to minimize the execution costs generated by mobile applications computation. The results of our simulations made in Matlab, showed that our proposed scheme can drastically decrease the energy consumption of intensive mobile application workload and speed up the execution of real time applications.
{"title":"Channel Allocation-Based Demand Assignment Reservation Protocol for Computation Offloading in Mobile Edge Computing","authors":"Empilo Eynthon Guillaume Nelson, Songtao Guo","doi":"10.1109/ICACI52617.2021.9435866","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435866","url":null,"abstract":"Considered as the key application of mobile edge computing (MEC), computation offloading emerges as a technology necessary to offload data for computation at an edge cloud. MEC is evolving as a promising technique susceptible to support resource constraint devices and delay sensitive applications, by delivering computing services nearby mobile users. Nevertheless, many studies have shown that latency remains one of the major challenges in MEC networks. However, in this paper, we propose to solve the latency challenge in mobile edge computing by developing the channel allocation-based demand assignment protocol for computation offloading (DAP-CO), and to tackle the server selection problem in a multi-edge server network so that to minimize the execution costs generated by mobile applications computation. The results of our simulations made in Matlab, showed that our proposed scheme can drastically decrease the energy consumption of intensive mobile application workload and speed up the execution of real time applications.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131147061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435858
Sokliep Pheng, Ji Li, Xiaonan Luo, Y. Zhong, Zetao Jiang
Indoor Positioning System (IPS) in generally perform as a network of devices that always located the objects or people inside a building wirelessly. An IPS has direction relies nearby anchors and also can be entirely local to your smartphone. With the rapid growth and sharp increase in Indoor Positioning System (IPS) demand in the world, there are a lot of researchers trying to invent new algorithm to develop IPS. This paper proposed the Bluetooth-Base Indoor Positioning Algorithm. The RF characteristics such as RSSI and WLAN RSSI fingerprinting system normally formed by two phases, fist is offline phase and second is online phase. Fingerprinting system handling both off-line and online data and estimate the user’s location. Our algorithm design is a collection of Weighted K-Nearest Neighbors (WKNN) and Filtering algorithms by KALMAN Filter. Finally, to avoid the problems of IPS and get a better accurate we proposed two algorithms: Weighted K-Nearest Neighbors Particle Filter (WKNNPF) and Weighted K-Nearest Neighbors Extended Kalman Filter (WKNNEKF) compare to KNN and WKNN result. After comparing we found that the result of WKNNPF and WKNNEKF is better result than KNN and WKNN. The Probability in 3M of WKNN is about 79%, WKNNEKF is about 89%, and WKNNPF is about 95.1%. Among one of the proposed algorithms WKNNPF is better than WKNNEKF on accuracy 1.7-2 meters with 42.2m/s response time.
{"title":"Bluetooth-Based WKNNPF and WKNNEKF Indoor Positioning Algorithm","authors":"Sokliep Pheng, Ji Li, Xiaonan Luo, Y. Zhong, Zetao Jiang","doi":"10.1109/ICACI52617.2021.9435858","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435858","url":null,"abstract":"Indoor Positioning System (IPS) in generally perform as a network of devices that always located the objects or people inside a building wirelessly. An IPS has direction relies nearby anchors and also can be entirely local to your smartphone. With the rapid growth and sharp increase in Indoor Positioning System (IPS) demand in the world, there are a lot of researchers trying to invent new algorithm to develop IPS. This paper proposed the Bluetooth-Base Indoor Positioning Algorithm. The RF characteristics such as RSSI and WLAN RSSI fingerprinting system normally formed by two phases, fist is offline phase and second is online phase. Fingerprinting system handling both off-line and online data and estimate the user’s location. Our algorithm design is a collection of Weighted K-Nearest Neighbors (WKNN) and Filtering algorithms by KALMAN Filter. Finally, to avoid the problems of IPS and get a better accurate we proposed two algorithms: Weighted K-Nearest Neighbors Particle Filter (WKNNPF) and Weighted K-Nearest Neighbors Extended Kalman Filter (WKNNEKF) compare to KNN and WKNN result. After comparing we found that the result of WKNNPF and WKNNEKF is better result than KNN and WKNN. The Probability in 3M of WKNN is about 79%, WKNNEKF is about 89%, and WKNNPF is about 95.1%. Among one of the proposed algorithms WKNNPF is better than WKNNEKF on accuracy 1.7-2 meters with 42.2m/s response time.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132186550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435868
Yiyuan Chai, Jiqiang Feng, Chen Xu, Sitian Qin
In this paper, a novel network flow is presented from a distributed perspective, which aims to solve classical Stein equation. With the coefficient matrices of appropriate dimensions, each agent only access to several row information. That is to say, a standard decomposition method is presented extensively, and then a distributed optimization problem to search least squares solution is proposed by introducing substitutive variables. We show the equivalence between solutions of distributed optimization problem and least squares solution of original Stein equation. Related convex analysis results show that the state solutions of the designed distributed network flow converge to the least squares solution of Stein equation. Finally, numerical results provide the viability of the designed distributed network flow.
{"title":"Distributed Network Flow to Solve Constrained Linear Matrix Equation","authors":"Yiyuan Chai, Jiqiang Feng, Chen Xu, Sitian Qin","doi":"10.1109/ICACI52617.2021.9435868","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435868","url":null,"abstract":"In this paper, a novel network flow is presented from a distributed perspective, which aims to solve classical Stein equation. With the coefficient matrices of appropriate dimensions, each agent only access to several row information. That is to say, a standard decomposition method is presented extensively, and then a distributed optimization problem to search least squares solution is proposed by introducing substitutive variables. We show the equivalence between solutions of distributed optimization problem and least squares solution of original Stein equation. Related convex analysis results show that the state solutions of the designed distributed network flow converge to the least squares solution of Stein equation. Finally, numerical results provide the viability of the designed distributed network flow.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114706992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-14DOI: 10.1109/ICACI52617.2021.9435916
Hongyan Yu, Bao-liang Zhang, Tong Wang, Jun Wang
This paper addresses the secure transmission problem of privacy information over a fading channel with an eavesdropper. A neural network model is proposed for solving the secrecy capacity maximization problems in real time. Unlike conventional power allocation strategies, a neurodynamic secure transmission approach is provided by the relation between KKT (Karush-Kuhn-Tucker) optimality conditions and the equilibrium point of a neural network. The transient behaviour of neural networks are showed, and the effectiveness of the neurodynamic approach is substantiated with a secrecy capacity maximization problem.
{"title":"Secrecy Capacity Maximization in Wireless Wiretap Channel: A Neurodynamic Optimization Approach","authors":"Hongyan Yu, Bao-liang Zhang, Tong Wang, Jun Wang","doi":"10.1109/ICACI52617.2021.9435916","DOIUrl":"https://doi.org/10.1109/ICACI52617.2021.9435916","url":null,"abstract":"This paper addresses the secure transmission problem of privacy information over a fading channel with an eavesdropper. A neural network model is proposed for solving the secrecy capacity maximization problems in real time. Unlike conventional power allocation strategies, a neurodynamic secure transmission approach is provided by the relation between KKT (Karush-Kuhn-Tucker) optimality conditions and the equilibrium point of a neural network. The transient behaviour of neural networks are showed, and the effectiveness of the neurodynamic approach is substantiated with a secrecy capacity maximization problem.","PeriodicalId":382483,"journal":{"name":"2021 13th International Conference on Advanced Computational Intelligence (ICACI)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132079911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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