Digital Signal Processing: Fundamentals, Applications, and Deep Learning
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...
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Elsevier Science & Technology
2025
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| Schlagworte: | |
| Zusammenfassung: | 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 |
| Beschreibung: | 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 |
| Beschreibung: | 450 gr |
| ISBN: | 9780443273353 |
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| 520 | |a 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 | ||
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| spelling | Tan, Li Verfasser aut Digital Signal Processing Fundamentals, Applications, and Deep Learning Elsevier Science & Technology 2025 450 gr txt rdacontent n rdamedia nc rdacarrier 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 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 bicssc bisacsh Jiang, Jean Sonstige oth |
| spellingShingle | Tan, Li Digital Signal Processing Fundamentals, Applications, and Deep Learning bicssc bisacsh |
| title | Digital Signal Processing Fundamentals, Applications, and Deep Learning |
| title_auth | Digital Signal Processing Fundamentals, Applications, and Deep Learning |
| title_exact_search | Digital Signal Processing Fundamentals, Applications, and Deep Learning |
| title_full | Digital Signal Processing Fundamentals, Applications, and Deep Learning |
| title_fullStr | Digital Signal Processing Fundamentals, Applications, and Deep Learning |
| title_full_unstemmed | Digital Signal Processing Fundamentals, Applications, and Deep Learning |
| title_short | Digital Signal Processing |
| title_sort | digital signal processing fundamentals applications and deep learning |
| title_sub | Fundamentals, Applications, and Deep Learning |
| topic | bicssc bisacsh |
| topic_facet | bicssc bisacsh |
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