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.
"synopsis" may belong to another edition of this title.
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # CX-9789819824175
Quantity: 15 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 52106628-n
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
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
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 52106628-n
Quantity: Over 20 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 52106628
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 52106628
Quantity: Over 20 available
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
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
Seller: CitiRetail, Stevenage, United Kingdom
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
Quantity: 1 available
Seller: Revaluation Books, Exeter, United Kingdom
Hardcover. Condition: Brand New. 396 pages. 6.00x0.64x9.00 inches. In Stock. Seller Inventory # x-9819824176
Quantity: 2 available
Seller: Rarewaves.com UK, London, United Kingdom
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