Digital Signal Processing with Matlab Examples, Volume 2: by Jose Maria Giron-Sierra

By Jose Maria Giron-Sierra

This is the second one quantity in a trilogy on smooth sign Processing. the 3 books offer a concise exposition of sign processing issues, and a consultant to aid person sensible exploration in accordance with MATLAB programs.

This moment e-book makes a speciality of contemporary advancements in accordance with the calls for of latest electronic applied sciences. it really is divided into components: the 1st half comprises 4 chapters at the decomposition and restoration of indications, with specific emphasis on photographs. In flip, the second one half comprises 3 chapters and addresses very important data-based activities, corresponding to adaptive filtering, experimental modeling, and classification.

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Extra resources for Digital Signal Processing with Matlab Examples, Volume 2: Decomposition, Recovery, Data-Based Actions

Sample text

From 2D to 3D, data separability . . . . . . . . . . . Kernel-SVM classification example . . . . . . . . . . Kernel PCA example . . . . . . . . . . . . . . . BSAS pseudo-code example . . . . . . . . . . . . . Example of E-M algorithm . . . . . . . . . . . . . Bayesian regression example . . . . . . . . . . . . Bayesian prediction/interpolation example . . . . . . . Kriging example . . . . . . . . . .

Hough photo projection example . . . . . . . . . . . Radon transform of a rectangle . . . . . . . . . . . . A phantom . . . . . . . . . . . . . . . . . . . Inverse Radon transform with filter . . . . . . . . . . Radon transform of a phantom . . . . . . . . . . . . Inverse Radon transform . . . . . . . . . . . . . . Image downsampling (causing shearing) example . . . . Image downsampling (quincunx) example . .

Gauss Process samples . . . . . . . . . . . . . . . Gauss Process regression . . . . . . . . . . . . . . Perceptron example. . . . . . . . . . . . . . . . Example of Eigenfaces for recognition . . . . . . . . . Example of Fisherfaces for recognition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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