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4 produkter
4 produkter
E-bok
Engelska, 2013766 kr
Läs direkt efter köp
Digital Signal Processing, Second Edition enables electrical engineers and technicians in the fields of biomedical, computer, and electronics engineering to master the essential fundamentals of DSP principles and practice. Many instructive worked examples are used to illustrate the material, and the use of mathematics is minimized for easier grasp of concepts. As such, this title is also useful to undergraduates in electrical engineering, and as a reference for science students and practicing engineers.The book goes beyond DSP theory, to show implementation of algorithms in hardware and software. Additional topics covered include 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, u-law, ADPCM, and multi-rate DSP and over-sampling ADC.New to this edition:- MATLAB projects dealing with practical applications added throughout the book- New chapter (chapter 13) covering sub-band coding and wavelet transforms, methods that have become popular in the DSP field- New applications included in many chapters, including applications of DFT to seismic signals, electrocardiography data, and vibration signals- All real-time C programs revised for the TMS320C6713 DSK- Covers DSP principles with emphasis on communications and control applications- Chapter objectives, worked examples, and end-of-chapter exercises aid the reader in grasping key concepts and solving related problems- Website with MATLAB programs for simulation and C programs for real-time DSP
E-bok
Engelska, 2018837 kr
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Digital Signal Processing: Fundamentals and Applications, Third Edition, not only introduces students to the fundamental principles of DSP, it also provides 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. The book goes beyond DSP theory, showing the implementation of algorithms in hardware and software.Additional topics covered include 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.- Covers DSP principles with an emphasis on communications and control applications- Includes chapter objectives, worked examples, and end-of-chapter exercises that aid the reader in grasping key concepts and solving related problems- Provides an accompanying website with MATLAB programs for simulation and C programs for real-time DSP- Presents new problems of varying types and difficulties
Häftad, Engelska, 2025
1 267 kr
Skickas inom 5-8 vardagar
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 intelligenceIncludes application examples using DSP techniques for deep learning neural networks to solve real-world problemsProvides a new chapter to cover principles of artificial neural networks and convolution neural networks with back-propagation algorithmsProvides 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/9780443273353Offers teaching support, including an image bank, full solutions manual, and MATLAB projects for qualified instructors, available for request at https://educate.elsevier.com/9780443273353
E-bok
Engelska, 20251 406 kr
Läs direkt efter köp
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