This monograph provides a comprehensive synthesis of recent research that demonstrates how deep learning methods can be effectively applied to achieve technological innovation in signal processing.
Deep Learning and Signal Processing takes the reader through the evolution of machine and deep learning, beginning with the foundations of neural networks to advanced architectures such as deep recursive cascaded convolutional neural networks (CNNs), and core deep learning principles, to cutting-edge applications. Practical case studies in multiple areas such as blind equalization, remote sensing image classification, motion deblurring, handwriting recognition, ADHD diagnosis, and more, are integrated with learning points throughout the book.
By bridging theory with real-world applications, the book equips engineering technicians, postgraduate students, researchers, and AI professionals with the expertise to overcome technological bottlenecks in applying deep learning to signal processing within their respective domains.
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Guo Yecai is Professor and doctoral advisor. He graduated from Anqing Normal University in 1986, majoring in physics. In 2003, he obtained a doctor's degree in underwater acoustic engineering from Northwest Polytechnical University. He is one of the winners of One Hundred Excellent Doctoral Dissertations in China, the academic and technical leader of Anhui Province in China, as well as currently the academic leader of Anhui Institute of Information Technology. Guo Yecai has presided over or undertaken more than 20 scientific research projects, such as special funds for National Excellent Doctoral Dissertation Authors, National Natural Science Foundation, as well as national and provincial teaching and research projects. He won more than 10 provincial science and technology achievement awards and teaching achievement awards and published a Nationally Planned Textbook and 5 provincial key textbooks. More than 50 patents have been authorized by the China National Intellectual Property Administration.
Ma Lixiang holds a PhD in Engineering and is both a Senior Engineer and Young Top-notch Talents under the High-end Talent Introduction and Cultivation Action Plan Project in Anhui Province, and currently serves as the Assistant to the President of Anhui Institute of Information Technology and the Executive Dean of the School of Electrical and Electronic Engineering at our university. He graduated from Shandong University with a bachelor's degree in 2008 and from the University of Chinese Academy of Sciences with a doctor's degree in 2013. His research interests include software-defined radio, radar signal processing, and the Internet of Things. Ma Lixiang has hosted provincial-level key research and development projects, participated in multiple provincial-level teaching and research projects, published more than 10 high-level papers, and won a first prize for teaching achievement awards in Anhui Province in China.
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Hardcover. Condition: new. Hardcover. This monograph provides a comprehensive synthesis of recent research that demonstrates how deep learning methods can be effectively applied to achieve technological innovation in signal processing.Deep Learning and Signal Processing takes the reader through the evolution of machine and deep learning, beginning with the foundations of neural networks to advanced architectures such as deep recursive cascaded convolutional neural networks (CNNs), and core deep learning principles, to cutting-edge applications. Practical case studies in multiple areas such as blind equalization, remote sensing image classification, motion deblurring, handwriting recognition, ADHD diagnosis, and more, are integrated with learning points throughout the book.By bridging theory with real-world applications, the book equips engineering technicians, postgraduate students, researchers, and AI professionals with the expertise to overcome technological bottlenecks in applying deep learning to signal processing within their respective domains. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9789819824175
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Hardback. Condition: New. This monograph provides a comprehensive synthesis of recent research that demonstrates how deep learning methods can be effectively applied to achieve technological innovation in signal processing.Deep Learning and Signal Processing takes the reader through the evolution of machine and deep learning, beginning with the foundations of neural networks to advanced architectures such as deep recursive cascaded convolutional neural networks (CNNs), and core deep learning principles, to cutting-edge applications. Practical case studies in multiple areas such as blind equalization, remote sensing image classification, motion deblurring, handwriting recognition, ADHD diagnosis, and more, are integrated with learning points throughout the book.By bridging theory with real-world applications, the book equips engineering technicians, postgraduate students, researchers, and AI professionals with the expertise to overcome technological bottlenecks in applying deep learning to signal processing within their respective domains. Seller Inventory # LU-9789819824175
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Hardcover. Condition: new. Hardcover. This monograph provides a comprehensive synthesis of recent research that demonstrates how deep learning methods can be effectively applied to achieve technological innovation in signal processing.Deep Learning and Signal Processing takes the reader through the evolution of machine and deep learning, beginning with the foundations of neural networks to advanced architectures such as deep recursive cascaded convolutional neural networks (CNNs), and core deep learning principles, to cutting-edge applications. Practical case studies in multiple areas such as blind equalization, remote sensing image classification, motion deblurring, handwriting recognition, ADHD diagnosis, and more, are integrated with learning points throughout the book.By bridging theory with real-world applications, the book equips engineering technicians, postgraduate students, researchers, and AI professionals with the expertise to overcome technological bottlenecks in applying deep learning to signal processing within their respective domains. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9789819824175
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Hardback. Condition: New. This monograph provides a comprehensive synthesis of recent research that demonstrates how deep learning methods can be effectively applied to achieve technological innovation in signal processing.Deep Learning and Signal Processing takes the reader through the evolution of machine and deep learning, beginning with the foundations of neural networks to advanced architectures such as deep recursive cascaded convolutional neural networks (CNNs), and core deep learning principles, to cutting-edge applications. Practical case studies in multiple areas such as blind equalization, remote sensing image classification, motion deblurring, handwriting recognition, ADHD diagnosis, and more, are integrated with learning points throughout the book.By bridging theory with real-world applications, the book equips engineering technicians, postgraduate students, researchers, and AI professionals with the expertise to overcome technological bottlenecks in applying deep learning to signal processing within their respective domains. Seller Inventory # LU-9789819824175
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