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Algorithmic Mechanism Design for Internet of Things Services Market : Design Incentive Mechanisms to Facilitate the Efficiency and Sustainability of IoT Ecosystem
Algorithmic Mechanism Design for Internet of Things Services Market : Design Incentive Mechanisms to Facilitate the Efficiency and Sustainability of IoT Ecosystem
Autore Jiao Yutao
Pubbl/distr/stampa Singapore : , : Springer Singapore Pte. Limited, , 2022
Descrizione fisica 1 online resource (120 pages)
Altri autori (Persone) WangPing
NiyatoDusit
Soggetto genere / forma Electronic books.
ISBN 9789811673535
9789811673528
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910510558203321
Jiao Yutao  
Singapore : , : Springer Singapore Pte. Limited, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Algorithmic mechanism design for internet of things services market : design incentive mechanisms to facilitate the efficiency and sustainability of IoT ecosystem. / / Yutao Jiao, Ping Wang and Dusit Niyato
Algorithmic mechanism design for internet of things services market : design incentive mechanisms to facilitate the efficiency and sustainability of IoT ecosystem. / / Yutao Jiao, Ping Wang and Dusit Niyato
Autore Jiao Yutao
Pubbl/distr/stampa Singapore : , : Springer Nature, , [2022]
Descrizione fisica 1 online resource (120 pages)
Disciplina 004.678
Soggetto topico Internet of things
Internet industry
Resource allocation
ISBN 981-16-7353-5
981-16-7352-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910743380403321
Jiao Yutao  
Singapore : , : Springer Nature, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Deep reinforcement learning for wireless communications and networking : theory, applications and implementation / / Dinh Thai Hoang [and four others]
Deep reinforcement learning for wireless communications and networking : theory, applications and implementation / / Dinh Thai Hoang [and four others]
Autore Hoang Dinh Thai <1986->
Edizione [First edition.]
Pubbl/distr/stampa Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023]
Descrizione fisica 1 online resource (291 pages)
Disciplina 006.31
Soggetto topico Reinforcement learning
Wireless communication systems
Soggetto non controllato Artificial Intelligence
Computer Networks
Computers
ISBN 1-119-87374-6
1-119-87368-1
1-119-87373-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover -- Title Page -- Copyright -- Contents -- Notes on Contributors -- Foreword -- Preface -- Acknowledgments -- Acronyms -- Introduction -- Part I Fundamentals of Deep Reinforcement Learning -- Chapter 1 Deep Reinforcement Learning and Its Applications -- 1.1 Wireless Networks and Emerging Challenges -- 1.2 Machine Learning Techniques and Development of DRL -- 1.2.1 Machine Learning -- 1.2.2 Artificial Neural Network -- 1.2.3 Convolutional Neural Network -- 1.2.4 Recurrent Neural Network -- 1.2.5 Development of Deep Reinforcement Learning -- 1.3 Potentials and Applications of DRL -- 1.3.1 Benefits of DRL in Human Lives -- 1.3.2 Features and Advantages of DRL Techniques -- 1.3.3 Academic Research Activities -- 1.3.4 Applications of DRL Techniques -- 1.3.5 Applications of DRL Techniques in Wireless Networks -- 1.4 Structure of this Book and Target Readership -- 1.4.1 Motivations and Structure of this Book -- 1.4.2 Target Readership -- 1.5 Chapter Summary -- References -- Chapter 2 Markov Decision Process and Reinforcement Learning -- 2.1 Markov Decision Process -- 2.2 Partially Observable Markov Decision Process -- 2.3 Policy and Value Functions -- 2.4 Bellman Equations -- 2.5 Solutions of MDP Problems -- 2.5.1 Dynamic Programming -- 2.5.1.1 Policy Evaluation -- 2.5.1.2 Policy Improvement -- 2.5.1.3 Policy Iteration -- 2.5.2 Monte Carlo Sampling -- 2.6 Reinforcement Learning -- 2.7 Chapter Summary -- References -- Chapter 3 Deep Reinforcement Learning Models and Techniques -- 3.1 Value‐Based DRL Methods -- 3.1.1 Deep Q‐Network -- 3.1.2 Double DQN -- 3.1.3 Prioritized Experience Replay -- 3.1.4 Dueling Network -- 3.2 Policy‐Gradient Methods -- 3.2.1 REINFORCE Algorithm -- 3.2.1.1 Policy Gradient Estimation -- 3.2.1.2 Reducing the Variance -- 3.2.1.3 Policy Gradient Theorem -- 3.2.2 Actor‐Critic Methods -- 3.2.3 Advantage of Actor‐Critic Methods.
3.2.3.1 Advantage of Actor‐Critic (A2C) -- 3.2.3.2 Asynchronous Advantage Actor‐Critic (A3C) -- 3.2.3.3 Generalized Advantage Estimate (GAE) -- 3.3 Deterministic Policy Gradient (DPG) -- 3.3.1 Deterministic Policy Gradient Theorem -- 3.3.2 Deep Deterministic Policy Gradient (DDPG) -- 3.3.3 Distributed Distributional DDPG (D4PG) -- 3.4 Natural Gradients -- 3.4.1 Principle of Natural Gradients -- 3.4.2 Trust Region Policy Optimization (TRPO) -- 3.4.2.1 Trust Region -- 3.4.2.2 Sample‐Based Formulation -- 3.4.2.3 Practical Implementation -- 3.4.3 Proximal Policy Optimization (PPO) -- 3.5 Model‐Based RL -- 3.5.1 Vanilla Model‐Based RL -- 3.5.2 Robust Model‐Based RL: Model‐Ensemble TRPO (ME‐TRPO) -- 3.5.3 Adaptive Model‐Based RL: Model‐Based Meta‐Policy Optimization (MB‐MPO) -- 3.6 Chapter Summary -- References -- Chapter 4 A Case Study and Detailed Implementation -- 4.1 System Model and Problem Formulation -- 4.1.1 System Model and Assumptions -- 4.1.1.1 Jamming Model -- 4.1.1.2 System Operation -- 4.1.2 Problem Formulation -- 4.1.2.1 State Space -- 4.1.2.2 Action Space -- 4.1.2.3 Immediate Reward -- 4.1.2.4 Optimization Formulation -- 4.2 Implementation and Environment Settings -- 4.2.1 Install TensorFlow with Anaconda -- 4.2.2 Q‐Learning -- 4.2.2.1 Codes for the Environment -- 4.2.2.2 Codes for the Agent -- 4.2.3 Deep Q‐Learning -- 4.3 Simulation Results and Performance Analysis -- 4.4 Chapter Summary -- References -- Part II Applications of DRL in Wireless Communications and Networking -- Chapter 5 DRL at the Physical Layer -- 5.1 Beamforming, Signal Detection, and Decoding -- 5.1.1 Beamforming -- 5.1.1.1 Beamforming Optimization Problem -- 5.1.1.2 DRL‐Based Beamforming -- 5.1.2 Signal Detection and Channel Estimation -- 5.1.2.1 Signal Detection and Channel Estimation Problem -- 5.1.2.2 RL‐Based Approaches -- 5.1.3 Channel Decoding.
5.2 Power and Rate Control -- 5.2.1 Power and Rate Control Problem -- 5.2.2 DRL‐Based Power and Rate Control -- 5.3 Physical‐Layer Security -- 5.4 Chapter Summary -- References -- Chapter 6 DRL at the MAC Layer -- 6.1 Resource Management and Optimization -- 6.2 Channel Access Control -- 6.2.1 DRL in the IEEE 802.11 MAC -- 6.2.2 MAC for Massive Access in IoT -- 6.2.3 MAC for 5G and B5G Cellular Systems -- 6.3 Heterogeneous MAC Protocols -- 6.4 Chapter Summary -- References -- Chapter 7 DRL at the Network Layer -- 7.1 Traffic Routing -- 7.2 Network Slicing -- 7.2.1 Network Slicing‐Based Architecture -- 7.2.2 Applications of DRL in Network Slicing -- 7.3 Network Intrusion Detection -- 7.3.1 Host‐Based IDS -- 7.3.2 Network‐Based IDS -- 7.4 Chapter Summary -- References -- Chapter 8 DRL at the Application and Service Layer -- 8.1 Content Caching -- 8.1.1 QoS‐Aware Caching -- 8.1.2 Joint Caching and Transmission Control -- 8.1.3 Joint Caching, Networking, and Computation -- 8.2 Data and Computation Offloading -- 8.3 Data Processing and Analytics -- 8.3.1 Data Organization -- 8.3.1.1 Data Partitioning -- 8.3.1.2 Data Compression -- 8.3.2 Data Scheduling -- 8.3.3 Tuning of Data Processing Systems -- 8.3.4 Data Indexing -- 8.3.4.1 Database Index Selection -- 8.3.4.2 Index Structure Construction -- 8.3.5 Query Optimization -- 8.4 Chapter Summary -- References -- Part III Challenges, Approaches, Open Issues, and Emerging Research Topics -- Chapter 9 DRL Challenges in Wireless Networks -- 9.1 Adversarial Attacks on DRL -- 9.1.1 Attacks Perturbing the State space -- 9.1.1.1 Manipulation of Observations -- 9.1.1.2 Manipulation of Training Data -- 9.1.2 Attacks Perturbing the Reward Function -- 9.1.3 Attacks Perturbing the Action Space -- 9.2 Multiagent DRL in Dynamic Environments -- 9.2.1 Motivations -- 9.2.2 Multiagent Reinforcement Learning Models.
9.2.2.1 Markov/Stochastic Games -- 9.2.2.2 Decentralized Partially Observable Markov Decision Process (DPOMDP) -- 9.2.3 Applications of Multiagent DRL in Wireless Networks -- 9.2.4 Challenges of Using Multiagent DRL in Wireless Networks -- 9.2.4.1 Nonstationarity Issue -- 9.2.4.2 Partial Observability Issue -- 9.3 Other Challenges -- 9.3.1 Inherent Problems of Using RL in Real‐Word Systems -- 9.3.1.1 Limited Learning Samples -- 9.3.1.2 System Delays -- 9.3.1.3 High‐Dimensional State and Action Spaces -- 9.3.1.4 System and Environment Constraints -- 9.3.1.5 Partial Observability and Nonstationarity -- 9.3.1.6 Multiobjective Reward Functions -- 9.3.2 Inherent Problems of DL and Beyond -- 9.3.2.1 Inherent Problems of DL -- 9.3.2.2 Challenges of DRL Beyond Deep Learning -- 9.3.3 Implementation of DL Models in Wireless Devices -- 9.4 Chapter Summary -- References -- Chapter 10 DRL and Emerging Topics in Wireless Networks -- 10.1 DRL for Emerging Problems in Future Wireless Networks -- 10.1.1 Joint Radar and Data Communications -- 10.1.2 Ambient Backscatter Communications -- 10.1.3 Reconfigurable Intelligent Surface‐Aided Communications -- 10.1.4 Rate Splitting Communications -- 10.2 Advanced DRL Models -- 10.2.1 Deep Reinforcement Transfer Learning -- 10.2.1.1 Reward Shaping -- 10.2.1.2 Intertask Mapping -- 10.2.1.3 Learning from Demonstrations -- 10.2.1.4 Policy Transfer -- 10.2.1.5 Reusing Representations -- 10.2.2 Generative Adversarial Network (GAN) for DRL -- 10.2.3 Meta Reinforcement Learning -- 10.3 Chapter Summary -- References -- Index -- EULA.
Record Nr. UNINA-9910830760503321
Hoang Dinh Thai <1986->  
Hoboken, New Jersey : , : John Wiley & Sons, Inc., , [2023]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Edge AI [[electronic resource] ] : Convergence of Edge Computing and Artificial Intelligence / / by Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen
Edge AI [[electronic resource] ] : Convergence of Edge Computing and Artificial Intelligence / / by Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen
Autore Wang Xiaofei
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (xvii, 149 pages)
Disciplina 006.3
Soggetto topico Artificial intelligence
Computer communication systems
Computer organization
Artificial Intelligence
Computer Communication Networks
Computer Systems Organization and Communication Networks
ISBN 981-15-6186-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I. Introduction and Fundamentals -- Chapter 1. Introduction -- Chapter 2. Fundamentals of Edge Computing -- Chapter 3. Fundamentals of Artificial Intelligence -- Part II. Artificial Intelligence and Edge Computing -- Chapter 4. Artificial Intelligence Applications on Edge -- Chapter 5. Artificial Intelligence Inference in Edge -- Chapter 6. Artificial Intelligence Training at Edge -- Chapter 7. Edge Computing for Artificial Intelligence -- Chapter 8. Artificial Intelligence for Optimizing Edge -- Part III. Challenges and Conclusions -- Chapter 9. Lessons Learned and Open Challenges -- Chapter 10. Conclusions.
Record Nr. UNINA-9910416083603321
Wang Xiaofei  
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Edge AI : Convergence of Edge Computing and Artificial Intelligence / / by Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen
Edge AI : Convergence of Edge Computing and Artificial Intelligence / / by Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen
Autore Wang Xiaofei
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Springer Singapore, 2020
Descrizione fisica 1 online resource (xvii, 149 pages)
Disciplina 006.3
Soggetto topico Artificial intelligence
Computer communication systems
Computer organization
Artificial Intelligence
Computer Communication Networks
Computer Systems Organization and Communication Networks
ISBN 981-15-6186-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I. Introduction and Fundamentals -- Chapter 1. Introduction -- Chapter 2. Fundamentals of Edge Computing -- Chapter 3. Fundamentals of Artificial Intelligence -- Part II. Artificial Intelligence and Edge Computing -- Chapter 4. Artificial Intelligence Applications on Edge -- Chapter 5. Artificial Intelligence Inference in Edge -- Chapter 6. Artificial Intelligence Training at Edge -- Chapter 7. Edge Computing for Artificial Intelligence -- Chapter 8. Artificial Intelligence for Optimizing Edge -- Part III. Challenges and Conclusions -- Chapter 9. Lessons Learned and Open Challenges -- Chapter 10. Conclusions.
Record Nr. UNISA-996465363903316
Wang Xiaofei  
Springer Singapore, 2020
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Edge AI : Convergence of Edge Computing and Artificial Intelligence / / by Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen
Edge AI : Convergence of Edge Computing and Artificial Intelligence / / by Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen
Autore Wang Xiaofei
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Springer Singapore, 2020
Descrizione fisica 1 online resource (xvii, 149 pages)
Disciplina 006.3
Soggetto topico Artificial intelligence
Computer networks
Computer organization
Artificial Intelligence
Computer Communication Networks
Computer Systems Organization and Communication Networks
ISBN 9789811561863
9811561869
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Part I. Introduction and Fundamentals -- Chapter 1. Introduction -- Chapter 2. Fundamentals of Edge Computing -- Chapter 3. Fundamentals of Artificial Intelligence -- Part II. Artificial Intelligence and Edge Computing -- Chapter 4. Artificial Intelligence Applications on Edge -- Chapter 5. Artificial Intelligence Inference in Edge -- Chapter 6. Artificial Intelligence Training at Edge -- Chapter 7. Edge Computing for Artificial Intelligence -- Chapter 8. Artificial Intelligence for Optimizing Edge -- Part III. Challenges and Conclusions -- Chapter 9. Lessons Learned and Open Challenges -- Chapter 10. Conclusions.
Record Nr. UNINA-9910863118103321
Wang Xiaofei  
Springer Singapore, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Radio resource management in multi-tier cellular wireless networks / / Ekram Hossain, University of Manitoba, Canada, Long Bao Le, INRS-EMT, Quebec, Canada, Dusit Niyato, Nanyang Technological University, Singapore
Radio resource management in multi-tier cellular wireless networks / / Ekram Hossain, University of Manitoba, Canada, Long Bao Le, INRS-EMT, Quebec, Canada, Dusit Niyato, Nanyang Technological University, Singapore
Autore Hossain Ekram <1971->
Edizione [1st edition.]
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , [2014]
Descrizione fisica 1 online resource (347 p.)
Disciplina 621.3845/6
Altri autori (Persone) NiyatoDusit
LeBao Long <1976->
Collana Adaptive and cognitive dynamic systems: signal processing, learning, communications and control
Soggetto topico Wireless communication systems
Femtocells
Radio resource management (Wireless communications)
ISBN 1-118-74977-4
1-118-74982-0
1-118-74946-4
Classificazione TEC041000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto -- PREFACE xv -- CHAPTER 1 OVERVIEW OF MULTI-TIER CELLULAR WIRELESS NETWORKS 1 -- CHAPTER 2 RESOURCE ALLOCATION APPROACHES IN MULTI-TIER NETWORKS 31 -- CHAPTER 3 RESOURCE ALLOCATION IN OFDMA-BASED MULTI-TIER CELLULAR NETWORKS 51 -- CHAPTER 4 RESOURCE ALLOCATION FOR CLUSTERED SMALL CELLS IN TWO-TIER OFDMA NETWORKS 84 -- CHAPTER 5 RESOURCE ALLOCATION IN TWO-TIER NETWORKS USING FRACTIONAL FREQUENCY REUSE 102 -- CHAPTER 6 CALL ADMISSION CONTROL IN FRACTIONAL FREQUENCY REUSE-BASED TWO-TIER NETWORKS 123 -- CHAPTER 7 GAME THEORETIC APPROACHES FOR RESOURCE MANAGEMENT IN MULTI-TIER NETWORKS 155 -- CHAPTER 8 RESOURCE ALLOCATION IN CDMA-BASED MULTI-TIER HETNETS 206 -- CHAPTER 9 SELF-ORGANIZING SMALL CELL NETWORKS 250 -- CHAPTER 10 RESOURCE ALLOCATION IN MULTI-TIER NETWORKS WITH COGNITIVE SMALL CELLS 302 -- INDEX 321
Record Nr. UNINA-9910139011803321
Hossain Ekram <1971->  
Hoboken, New Jersey : , : Wiley, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Radio resource management in multi-tier cellular wireless networks / / Ekram Hossain, University of Manitoba, Canada, Long Bao Le, INRS-EMT, Quebec, Canada, Dusit Niyato, Nanyang Technological University, Singapore
Radio resource management in multi-tier cellular wireless networks / / Ekram Hossain, University of Manitoba, Canada, Long Bao Le, INRS-EMT, Quebec, Canada, Dusit Niyato, Nanyang Technological University, Singapore
Autore Hossain Ekram <1971->
Edizione [1st edition.]
Pubbl/distr/stampa Hoboken, New Jersey : , : Wiley, , [2014]
Descrizione fisica 1 online resource (347 p.)
Disciplina 621.3845/6
Altri autori (Persone) NiyatoDusit
LeBao Long <1976->
Collana Adaptive and cognitive dynamic systems: signal processing, learning, communications and control
Soggetto topico Wireless communication systems
Femtocells
Radio resource management (Wireless communications)
ISBN 1-118-74977-4
1-118-74982-0
1-118-74946-4
Classificazione TEC041000
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto -- PREFACE xv -- CHAPTER 1 OVERVIEW OF MULTI-TIER CELLULAR WIRELESS NETWORKS 1 -- CHAPTER 2 RESOURCE ALLOCATION APPROACHES IN MULTI-TIER NETWORKS 31 -- CHAPTER 3 RESOURCE ALLOCATION IN OFDMA-BASED MULTI-TIER CELLULAR NETWORKS 51 -- CHAPTER 4 RESOURCE ALLOCATION FOR CLUSTERED SMALL CELLS IN TWO-TIER OFDMA NETWORKS 84 -- CHAPTER 5 RESOURCE ALLOCATION IN TWO-TIER NETWORKS USING FRACTIONAL FREQUENCY REUSE 102 -- CHAPTER 6 CALL ADMISSION CONTROL IN FRACTIONAL FREQUENCY REUSE-BASED TWO-TIER NETWORKS 123 -- CHAPTER 7 GAME THEORETIC APPROACHES FOR RESOURCE MANAGEMENT IN MULTI-TIER NETWORKS 155 -- CHAPTER 8 RESOURCE ALLOCATION IN CDMA-BASED MULTI-TIER HETNETS 206 -- CHAPTER 9 SELF-ORGANIZING SMALL CELL NETWORKS 250 -- CHAPTER 10 RESOURCE ALLOCATION IN MULTI-TIER NETWORKS WITH COGNITIVE SMALL CELLS 302 -- INDEX 321
Record Nr. UNINA-9910810197303321
Hossain Ekram <1971->  
Hoboken, New Jersey : , : Wiley, , [2014]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Realizing the Metaverse : A Communications and Networking Perspective
Realizing the Metaverse : A Communications and Networking Perspective
Autore Lim Wei Yang Bryan
Edizione [1st ed.]
Pubbl/distr/stampa Newark : , : John Wiley & Sons, Incorporated, , 2024
Descrizione fisica 1 online resource (206 pages)
Disciplina 302.23/1
Altri autori (Persone) XiongZehui
NiyatoDusit
ZhangJunshan
ShenXuemin
Soggetto topico Metaverse
Digital communications - Social aspects
Digital communications - Technological innovations
Computer networks - Access control
Computer security
ISBN 9781394188918
1394188919
9781394188925
1394188927
9781394188932
1394188935
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Communication and computing in edge-enabled Metaverse -- Advanced and future network access technologies for the Metaverse -- How to intelligentize the Metaverse -- How to transact in the Metaverse -- How to secure the Metaverse.
Record Nr. UNINA-9911019674503321
Lim Wei Yang Bryan  
Newark : , : John Wiley & Sons, Incorporated, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Wireless Semantic Communications : Concepts, Principles, and Challenges
Wireless Semantic Communications : Concepts, Principles, and Challenges
Autore Sun Yao
Edizione [1st ed.]
Pubbl/distr/stampa Newark : , : John Wiley & Sons, Incorporated, , 2024
Descrizione fisica 1 online resource (225 pages)
Altri autori (Persone) ZhangLan
NiyatoDusit
ImranMuhammad Ali
ISBN 1-394-22331-5
1-394-22332-3
1-394-22333-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910889693703321
Sun Yao  
Newark : , : John Wiley & Sons, Incorporated, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui