MODELING AND OPTIMIZATION OF SIGNALS USING MACHINE LEARNING TECHNIQUES (HB 2024). Este artículo no está disponible.
Idioma: inglés
Editorial: JOHN WILEY NP (ORIGINAL)45, 2024
- Tapa dura
- Usado

Librería: UK BOOKS STORE, London, London, Reino UnidoUK BOOKS STORE
Vendedor de AbeBooks desde el 11 de marzo de 2024
Condición: Usado
EUR 321,22
Descripción del artículo del vendedor
Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
N° de ref. del artículo CBS 9781119847687
- Título
- MODELING AND OPTIMIZATION OF SIGNALS USING MACHINE LEARNING TECHNIQUES (HB 2024)
- Autor
- SINGH C.
- Editorial
- JOHN WILEY NP (ORIGINAL)45
- Año de publicación
- 2024
- Estado
- New Books
- Encuadernación
- Encuadernación de tapa dura
- Idioma
- inglés
- ISBN 10
- 1119847680
- ISBN 13
- 9781119847687
- Edición
- Edición Internacional
Explore the power of machine learning to revolutionize signal processing and optimization with cutting-edge techniques and practical insights in this outstanding new volume from Scrivener Publishing.
Modeling and Optimization of Signals using Machine Learning Techniques is designed for researchers from academia, industries, and R&D organizations worldwide who are passionate about advancing machine learning methods, signal processing theory, data mining, artificial intelligence, and optimization. This book addresses the role of machine learning in transforming vast signal databases from sensor networks, internet services, and communication systems into actionable decision systems. It explores the development of computational solutions and novel models to handle complex real-world signals such as speech, music, biomedical data, and multimedia.
Through comprehensive coverage of cutting-edge techniques, this book equips readers with the tools to automate signal processing and analysis, ultimately enhancing the retrieval of valuable information from extensive data storage systems. By providing both theoretical insights and practical guidance, the book serves as a comprehensive resource for researchers, engineers, and practitioners aiming to harness the power of machine learning in signal processing.
Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Chandra Singh is an assistant professor in the Department of Electronics and Communication Engineering at Sahyadri College of Engineering and Management, Mangalore, India, and is pursuing a PhD from VTU Belagavi, India. He has four patents, he has published over 25 papers in scientific journals, and he is the editor of seven books.
Rathishchandra R. Gatti, PhD, is an associate professor at Jawaharlal Nehru University, Delhi, India. With over 20 years of industrial, research, and teaching experience under his belt, he also has four patents, has published over 40 papers in scientific journals, and is the editor of seven research books and one journal.
K.V.S.S.S.S.SAIRAM, PhD, is a professor and Head of the Electronics and Communication Engineering Department at the NMAM Institute of Technology, Nitte, India. He has 25 years of experience in teaching and research and has published over 50 papers in international journals and conferences. He is also a reviewer for several journals.
Manjunatha Badiger, PhD, is an assistant professor at Sahyadri College of Engineering and Management, Adyar, Mangalore, Karnataka, India. He has over 12 years of experience in academics, research, and administration. He earned his PhD in machine learning in 2024 at Visvesvaraya Technological University.
Naveen Kumar S., MTech, is an assistant professor at the Sahyadri College of Engineering and Management. Previously he was an assistant professor at JSS Academy of Technical Education, Noida, India. He obtained his MTech in automotive electronics from Sri Jayachamarajendra College of Engineering, Mysore, India.
Varun Saxena, PhD, received his PhD in electromagnetic ion traps from IIT Delhi, New Delhi, in 2018. He is currently an assistant professor at the School of Engineering, Jawaharlal Nehru University, New Delhi.
“Acerca de” puede pertenecer a otra edición de este título.