• Contact

  • Newsletter

  • About us

  • Delivery options

  • News

  • 0
    Digital Signal Processing: Fundamentals, Applications, and Deep Learning

    Digital Signal Processing by Tan, Li; Jiang, Jean;

    Fundamentals, Applications, and Deep Learning

      • GET 10% OFF

      • The discount is only available for 'Alert of Favourite Topics' newsletter recipients.
      • Publisher's listprice EUR 112.99
      • The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.

        47 930 Ft (45 647 Ft + 5% VAT)
      • Discount 10% (cc. 4 793 Ft off)
      • Discounted price 43 136 Ft (41 082 Ft + 5% VAT)

    47 930 Ft

    db

    Availability

    Not yet published.

    Why don't you give exact delivery time?

    Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.

    Product details:

    • Edition number 4
    • Publisher Academic Press
    • Date of Publication 30 May 2025

    • ISBN 9780443273353
    • Binding Paperback
    • No. of pages1032 pages
    • Size 235x191 mm
    • Weight 2060 g
    • Language English
    • 700

    Categories

    Long description:

    Digital Signal Processing: Fundamentals, Applications, and Deep Learning, Fourth Edition introduces students to the fundamental principles of digital signal processing (DSP) while also providing a working knowledge that they take with them into their engineering careers. Many instructive, worked examples are used to illustrate the material, and the use of mathematics is minimized for an easier grasp of concepts. As such, this title is also useful as a reference for non-engineering students and practicing engineers.

    This book goes beyond DSP theory, showing the implementation of algorithms in hardware and software. Additional topics covered include DSP for artificial intelligence, adaptive filtering with noise reduction and echo cancellations, speech compression, signal sampling, digital filter realizations, filter design, multimedia applications, over-sampling, etc. More advanced topics are also covered, such as adaptive filters, speech compression such as pulse-code modulation, µ-law, adaptive differential pulse-code modulation, multi-rate DSP, oversampling analog-to-digital conversion, sub-band coding, wavelet transform, and neural networks.




    • Covers DSP principles with various examples of real-world DSP applications on noise cancellation, communications, control applications, and artificial intelligence
    • Includes application examples using DSP techniques for deep learning neural networks to solve real-world problems
    • Provides a new chapter to cover principles of artificial neural networks and convolution neural networks with back-propagation algorithms
    • Provides hands-on practice, with MATLAB code for worked examples and C programs for real-time DSP for students at https://www.elsevier.com/books-and-journals/book-companion/9780443273353
    • Offers teaching support, including an image bank, full solutions manual, and MATLAB projects for qualified instructors, available for request at https://educate.elsevier.com/9780443273353

    More

    Table of Contents:

    1. Introduction to Digital Signal Processing
    2. Signal Sampling and Quantization
    3. Digital Signals and Systems
    4. Discrete Fourier Transform and Signal Spectra
    5. The z-Transform
    6. Digital Signal Processing Systems, Basic Filtering Types, and Digital Filter Realizations
    7. Finite Impulse Response Filter Design
    8. Infinite Impulse Response Filter Design
    9. Adaptive Filters and Applications
    10. Waveform Quantization and Compression
    11. Multirate Digital Signal Processing, Oversampling of Analog-to-Digital Conversion, and Undersampling of Bandpass Signals
    12. Subband and Wavelet-Based Coding
    13. Image Processing Basics
    14. Digital Signal Processing for Artificial Intelligence
    15. Hardware and Software for Digital Signal Processors

    More