Signal Processing Roadmap
Morgan Kaufmann Publishers In (Verlag)
978-0-443-33172-5 (ISBN)
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In addition to covering uncertainty modeling and key signal processing considerations, the book delves into the latest developments in hybrid information system modeling, emphasizing its practical uses in fields like finance, healthcare, and engineering. Readers will find detailed case studies that illustrate how these models address complex, real-world problems. The text also thoroughly reviews foundational theories related to non-linear optimization, fuzzy sets, and rough sets.
Dr. Pushan Kumar Dutta is an Assistant Professor Grade III at Amity University Kolkata, specializing in Electronics and Communication Engineering. He holds a Ph.D. in Electronics and Telecommunication Engineering from Jadavpur University and completed a Postdoctoral fellowship as an Erasmus Mundus Scholar at the University of Oradea. His research interests include data mining, AI, edge computing, and predictive analytics, focusing on applications in smart cities, healthcare, and sustainable development. Dr. Dutta has published over 114 articles in Scopus-indexed journals and has edited more than 30 books for prestigious publishers in 2023-2024. He is recognized as a reviewer for leading academic publishers and has received accolades such as the 'Mentor of Change' from NITI Aayog. Committed to innovative teaching, he authored "Innovative Digital Teaching and Learning for Professional Readiness" and holds two Indian patents. Dr. Dutta is a Threws Fellow member and a senior member of the Indian Institute of Engineering. Pethuru Raj PhD works as chief architect and vice president of site reliability engineering (SRE) division of Reliance Jio Infocomm. Ltd. Bangalore. Previously he worked as a cloud infrastructure architect in the IBM Global Cloud Center of Excellence (CoE), Bangalore. He worked as a TOGAF-certified enterprise architecture (EA) consultant in Wipro Consulting Services (WCS) Division and as a lead architect in the corporate research (CR) division of Robert Bosch, India. He has gained more than 18 years of IT industry experience. He finished the CSIR-sponsored PhD degree in Anna University, Chennai and continued the UGC-sponsored postdoctoral research in the department of Computer Science and Automation, Indian Institute of Science, Bangalore. Thereafter, he was granted a couple of international research fellowships (JSPS and JST) to work as a research scientist for 3.5 years in two leading Japanese universities. He has authored and edited 18 books thus far and he focuses on some of the emerging technologies such as Containerized Clouds; Big, Fast, and Streaming Data Analytics; Microservices architecture (MSA); Machine and Deep Learning Algorithms; Blockchain Technology; The Internet of Things; and Edge Computing. He has published more than 30 research papers in peer-reviewed journals such as IEEE, ACM, Springer-Verlag, Inderscience, etc. Pronaya Bhattacharya received the Ph.D. degree in optical networks from Dr. A. P. J. Abdul Kalam Technical University, Lucknow, Uttar Pradesh, India, in 2021. He is currently employed as an Assistant Professor with the Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad, India. He has over eight years of teaching experience. He has authored or coauthored more than 120 research papers in leading SCI journals and top core IEEE COMSOC A* conferences. Some of his findings are published in reputed SCI journals, like IEEE Journal of Biomedical and Health Informatics, IEEE Transactions on Vehicular Technology, IEEE Internet of Things Journal, IEEE Transactions on Network Science and Engineering, IEEE Access, ETT (Wiley), Expert Systems (Wiley), FGCS (Elsevier), OQEL (Springer), WPC (Springer), ACM-MOBICOM, IEEE-INFOCOM, IEEE-ICC, IEEECITS, IEEE-ICIEM, IEEE-CCCI, and IEEE-ECAI. His research interests include healthcare analytics, optical switching and networking, federated learning, blockchain, and the IoT. Dr. Ishan Budhiraja earned his Ph.D. in Computer Science Engineering from the Thapar Institute of Engineering and Technology, Patiala, India in 2021. He received M.Tech. and B. Tech degree in Electronics and Communication Engineering from Maharishi Dayanand University, Rohtak, Haryana, in 2012 and Uttar Pradesh Technical University, Lucknow, India, in 2008, respectively. He worked as a Research Associate on the project Energy Management of Smart Home using cloud Infrastructure-A Utility Perspective, funded by CSIR, New Delhi, India. Some of his research findings are published in top-cited journals, such as IEEE Transactions on Industrial Informatics, IEEE Transactions on Vehicular Technology, IEEE Transactions on Mobile Computing, IEEE Internet of Things, IEEE Wireless Communication Magazine, IEEE Systems Journal, and various international top-tiered conferences, such as IEEE GLOBECOM, IEEE ICC, IEEE WCMC, ACM, and IEEE Infocom. His research interests include device-to-device communications, the Internet of Things, Non-orthogonal multiple access, femtocells, deep reinforcement learning, and microstrip patch antenna. KAPLUN DMITRII I. PhD (2009), Associate Professor (2015), Lead Researcher (2020) at Saint Petersburg Electrotechnical University “LETI (Saint Petersburg, Russia), Full Professor (2023) at China University of Mining and Technology. In 2009 he defended his PhD thesis in digital signal processing at Saint Petersburg Electrotechnical University “LETI. The current research and academic work are related with digital signal and image processing, embedded and reconfigurable systems, computer vision and machine learning. D. Kaplun regularly takes part in various interdisciplinary projects related to the use of computer vision and machine learning for biomedical data processing. The most substantial results are in the fields of digital signal and image processing, embedded systems and machine learning. Author of more than 100 papers in journals, including leading journals, and conference proceedings. He is an Associate/Guest Editor/Editorial Board Member such journals as Frontiers in Neuroinformatics, Industrial Artificial Intelligence, Scientific Reports, Signals.
1. Foundations of Signal Processing: A Comprehensive Overview
2. Frontiers in Digital and Analog Signal Processing Circuits and Systems in the era of Artificial Intelligence (AI)
3. Sustainable 6G Connectivity through AI-Powered Energy Efficiency
4. Computing Requirements and Techniques to Support Signal Processing
5. Signal Processing: Potential Applications, Trends, and Challenges
6. Signal Processing for Localization and Sensing Techniques in Next Generation Wireless Networks (NWGNs)
7. Advanced Signal Processing Techniques for Non-Orthogonal Multiple Access in 6G Networks
8. Signal Processing Innovations for improved 6G ubiquitous connectivity: Paving the path towards integrated Space-Ground-Underwater Networks
9. Advanced real-time signal processing techniques for adaptive beamforming in Beyond 5G wireless networks
10. Signal Processing for Autonomous Systems and Robotics: Principles, Techniques, and Future Directions
11. Signal Processing: A roadmap towards Image Reconstruction and Image Enhancement
12. Study of Image Enhancement Techniques for Satellite Images
13. Intelligent Signal Processing for Physical and MAC Layers: A Machine Learning Perspective
14. Optimization Techniques for 6G Communications: A Deep Learning Perspective
15. Advanced Image Restoration via Lightweight Convolutional Networks and Graph-Based Contextual Learning
16. Emerging Trends in Edge AI-Oriented Signal Processing for Internet of Things (IoT) Devices
17. Quantum-Enhanced Fuzzy Convolutional Neural Networks for High-Performance Analog Signal Processing Systems
18. Resource Optimization, Error Mitigation and Algorithmic Partitioning in Multi-Node Quantum Systems: A Practical Perspective
19. AI-Driven HetNet Optimization: Composite Fading, Mobility Modelling, and Resource Allocation
20. Intelligent Traffic Management System with Machine Learning for Congestion Prediction and Control
| Erscheint lt. Verlag | 1.3.2026 |
|---|---|
| Reihe/Serie | Computational Modeling Applications for Existential Risks |
| Verlagsort | San Francisco |
| Sprache | englisch |
| Maße | 191 x 235 mm |
| Gewicht | 450 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Software Entwicklung |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 0-443-33172-3 / 0443331723 |
| ISBN-13 | 978-0-443-33172-5 / 9780443331725 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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