Bookbot

Digital Signal Processing

Fundamentals, Applications, and Deep Learning - Fourth Edition

En savoir plus sur le livre

Digital Signal Processing: Fundamentals, Applications, and Deep Learning, Fourth Edition introduces students to the fundamental principles of DSP while also providing a working knowledge they can 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 book is also useful as a reference for non-engineering students and practicing engineers. The 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 PCM, µ-law, ADPCM, and multi-rate DSP, over-sampling ADC subband coding, and wavelet transform.

Édition

Achat du livre

Digital Signal Processing, Lizhe Tan, Jean Jiang

Langue
Année de publication
2025
product-detail.submit-box.info.binding
(souple)
Cet exemplaire n’est plus disponible.
ou
Voir l'édition disponible

Modes de paiement

Personne n'a encore évalué .Évaluer

Sous-titre
Fundamentals, Applications, and Deep Learning - Fourth Edition
Langue
Anglais
Publié
2025
Format
souple
Pages
960
ISBN10
0443273359
ISBN13
9780443273353
Séries
Description
Digital Signal Processing: Fundamentals, Applications, and Deep Learning, Fourth Edition introduces students to the fundamental principles of DSP while also providing a working knowledge they can 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 book is also useful as a reference for non-engineering students and practicing engineers. The 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 PCM, µ-law, ADPCM, and multi-rate DSP, over-sampling ADC subband coding, and wavelet transform.