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Covers all major DSP topics Full of insider information and shortcuts Basic techniques and algorithms explained without complex numbers.

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Mathematics of Signal Processing - Gilbert Strang

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The Scientist and Engineer's Guide to Digital Signal Processing | BibSonomy

Your review was sent successfully and is now waiting for our team to publish it. Reviews 0. Chapter 2 - Statistics, Probability and Noise. Chapter 20 - Chebyshev Filters. Chapter 21 - Filter Comparison.

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Chapter 22 - Audio Processing. Chapter 23 - Image Formation Display. Chapter 24 - Linear Image Processing. Chapter 25 - Special Imaging Techniques.

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Chapter 26 - Neural Networks and more! Chapter 27 - Data Compression. Chapter 28 - Digital Signal Processors. Chapter 30 - Complex Numbers. Chapter 31 - The Complex Fourier Transform. Active 1 year ago. Viewed 2k times. Aside from reading DSP.


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Glorfindel 1 1 gold badge 2 2 silver badges 9 9 bronze badges. FIR is, DFT, quantization error, etc are timeless concepts that are no different now than in the 80's. So, this depends a lot on what you know about math so far.


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From the CS students I know, about a half have actually taken the same math as math students for the first two semesters that being Analysis and Linear Algebra , which actually is an excellent base for learning DSP, as these are very familiar with concepts like vector spaces, convergence, differentiability etc. Look around for well-reputed universities with an electrical engineering degree that have a public description or maybe even publicly available lectures!

Go, figure out the dependencies of exactly that course, and learn them, then learn the contents of that course, is what I'd recommend. Richard Lyons Richard Lyons 2, 7 7 silver badges 18 18 bronze badges. I didn't know about the Orfanidis resource, that is great, thank you.

The Scientist and Engineer's Guide to Digital Signal Processing

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