Deep Learning And Signal Processing

Bibliographic Details
Title: Deep Learning And Signal Processing
Description: 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.
Authors: Yecai Guo, Lixiang Ma
Resource Type: eBook.
Subjects: Signal processing--Data processing, Deep learning (Machine learning)
Categories: COMPUTERS / Data Science / Machine Learning, TECHNOLOGY & ENGINEERING / Signals & Signal Processing
Database: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 4494004
RelevancyScore: 987
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 987.310668945313
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  Data: Deep Learning And Signal Processing
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  Data: 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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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=4494004
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Signal processing--Data processing
        Type: general
      – SubjectFull: Deep learning (Machine learning)
        Type: general
    Titles:
      – TitleFull: Deep Learning And Signal Processing
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yecai Guo
      – PersonEntity:
          Name:
            NameFull: Lixiang Ma
      – PersonEntity:
          Name:
            NameFull: Yecai Guo
      – PersonEntity:
          Name:
            NameFull: Lixiang Ma
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2026
            – D: 25
              M: 05
              Type: profile
              Y: 2026
          Identifiers:
            – Type: isbn-print
              Value: 9789819824175
            – Type: isbn-electronic
              Value: 9789819824182
          Titles:
            – TitleFull: Deep Learning And Signal Processing
              Type: main
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