# Tag Info

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Assuming you have completed Oppenheim's Discrete-Time Signal Processing book then the next (advanced) step could be anyone of the followings: (assumes a graduate level Linear System Theory background) Statistical Digital Signal Processing, Monson Hayes Multiresolution Signal Decomposition: Transforms, Subbands,Wavelets, A.Akansu Adaptive Filter Theory, ...

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I myself recently graduated from Applied Mathematics and began PhD in signal processing. I do Stochastic Geometry modeling of wireless networks in particular, which is quite mathematical subject. It involves measure theory, probability theory, Fourier Analysis etc. etc. The area of Signal Processing is very broad indeed. It of course depends if you want to ...

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Linear Signals and systems by Lathi Check out MIT lectures of Prof. Oppenheim too. Those were super helpful.

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My book "Understanding Digital Signal Processing" introduces the mathematics of DSP in a gentle and illuminating way. Each math equation is explained in understandable text. My book does not choke the reader to death with algebra. Steven Smith's terrific "The Scientist and Engineer's Guide to Digital Signal Processing" book is modest in its mathematical ...

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There are few options: Stephen Boyd, Lieven Vandenberghe - Convex Optimization. This is the classic in this field. Very well written book. Also have a look on other papers of Boyd on similar subjects such as the The Alternating Direction Method of Multipliers (ADMM). They also have a great MOOC Course Stanford Online CVX 101 - Convex Optimization. Amir Beck ...

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You can't escape understanding some basic calculus stuff to understand the concept of fourier transform and DTFT. And if you want to understand statistical DSP you need to understand probability, and linear algebra is so widely used you really need to understand that.

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IMHO the best book that relates circuits to the z-transform is Papoulis, "Circuits and Systems: A Modern Approach". You can find it used for a handful of dollars.

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This is the list I'd recommend: Rafael C. Gonzalez, Richard E. Woods - Digital Image Processing Great introductory book. Well written, a lot of examples. Though it is not deep in any of the fields. Alan C. Bovik - The Essential Guide to Image Processing A comprehensive book on many image processing related subjects. Gret book to skim through. Richard ...

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A fundamental book on image processing for electrical engineers is Two-Dimensional Signal and Image Proccesing_Jae S. Lim A highly recommended one, again, for electrical engineers is Fundamentals of Digital Image Processing_Anil Jain A hands-on book on basic practical image procesing is Principles of Digital Image Processing_Wilhelm Burger If ...

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Signal denosing is a well-studied technique in signal processing. It first began using simple techniques such as filtering. In this approach, the emphasis is laid on designing filters which can perform denosing techniques in a fast and efficient manner. Later, when wavelet theory was developed, some researchers used wavelets to denosing the signal. ...

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i think it's because poles are more important than zeros. the location of the poles determine the stability of the system. when partial fraction expansion, it's the poles that survive in the partial fractions. it's the dominant poles that determine the decay rate of the impulse response (or any response after the input goes to zero). and it's in the ...

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My suspicion is that this ordering comes from the difference equation, which in most texts precedes the $\mathcal Z$-transform: $$a_0 y[n] + a_1 y[n-1] + \cdots = b_0 x[n] + b_1 x[n-1] + \cdots$$

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Understanding Digital Signal Processing from Lyons Signal Processing First from McClellan

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A good place to start is Van Diggelen and Enge's old course, now on YouTube. There's a lot of GNSS related information on Wikipedia but I would look at Navipedia first. Finally, you could try one of open source software receivers, the most comprehensive being gnss-sdr.

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Phasors are useful for the analysis of (real-valued) linear time-invariant (LTI) systems. A phasor is a complex number $$C=|C|e^{j\phi}=A+jB\tag{1}$$ which represents a sinusoidal signal: $$x(t)=\textrm{Re}\big\{Ce^{j\omega t}\big\}=A\cos(\omega t)-B\sin(\omega t)=|C|\cos(\omega t+\phi)\tag{2}$$ That's already the end of the story. Eq. $(2)$ is the generally ...

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The answer to my question is: Essentials of Digital Signal Processing 1st Edition by B. P. Lathi https://www.amazon.com/gp/product/1107059321/ref=ppx_yo_dt_b_asin_title_o00_s00?ie=UTF8&psc=1 where in Section 6.6 you can find detailed discussions and good examples.

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digital signal processing by sk mitra

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Some video lectures, books (Analyzing neural time series data) from Mike x Cohen are good resources to learn Signal Processing. He also gives and explains Matlab examples. You can check it out here: https://www.mikexcohen.com/

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“Adaptive Filter Theory” by Simon Haykin is a classic text for all things adaptive filtering/noise reduction. The text is pretty heavy on math, but I think if you’re looking to actually understand how and why these methods work, it’s a great place to start. This is pretty much the standard for graduate classes in adaptive filtering. The techniques in the ...

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Possibly a pseudo-Darwinian effect, related to the autoregressive or all-pole models, and the initial letter 'a', the first of the alphabet. Details follow. This question made me dig into early works related to the (re)-discovery and usage of the $z$-transform for the representation of systems. Apparently, the concept of the $z$-transform was known to ...

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There are a number of books in addition to Zölzer's DAFX, the one I would recommend is: The Audio Programming Book by Boulanger... Also have a look at these: Designing Sound by Farnell Designing Audio Effect Plug-Ins in C++ by Pirkle Designing Software Synthesizer Plug-Ins in C++ by Pirkle

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I highly recommend you the book Schaum's outlines of Analog and Digital Communications. It will be the fastest refresher for the signal processing and probability concepts which are essential prerequisites for digital communications. It's not using that heavy math also, nevertheless, not a trivial one either ;-)

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