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 Free Download MathWorks MATLAB R2024a macOs (Apple Silicon) with Documentation | 16.7 Gb MathWorksunveiledRelease 2024a (R2024a) of the MATLAB and Simulink product families. R2024a introduces new functionality that streamlines the workflows of engineers and researchers working on AI and Wireless Communications systems. Owner:Mathworks Product Name:Matlab & Simulink Version:R2024a (24.1.0.2537033) with Documentation * Supported Architectures:x64 Website Home Page :www.mathworks.com Languages Supported:english System Requirements:macOs (Apple Silicon) * Size:16.7 Gb Installing local documentation: 1. mount the image R2024a_Doc_macOSAppleSilicon.dmg 2. execute in terminal Code: cd /Volumes/R2024a_Doc_macOSAppleSilicon/bin/maca64/ Code: ./mpm install-doc -matlabroot="/Applications/MATLAB_R2024a.app" -destination="/Applications/MATLAB_R2024a.app" The documentation will be installed in the /Applications/MATLAB_R2024a.app/help folder  Free Download Martin Trauth, E. Sillmann, R. Gebbers, "MATLAB® Recipes for Earth Sciences" English | 2010 | pages: 343 | ISBN: 3642447163 | PDF | 11,1 mb MATLAB® is used for a wide range of applications in geosciences, such as image processing in remote sensing, the generation and processing of digital elevation models, and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB, such as basic statistics for univariate, bivariate and multivariate datasets, jackknife and bootstrap resampling schemes, processing of digital elevation models, gridding and contouring, geostatistics and kriging, processing and georeferencing of satellite images, digitizing from the screen, linear and nonlinear time-series analysis, and the application of linear time-invariant and adaptive filters. The revised and updated Third Edition includes ten new sections and has greatly expanded on most chapters from the previous edition, including a step by step discussion of all methods before demonstrating the methods with MATLAB functions. New sections include: Data Storage and Handling, Data Structures and Classes of Objects, Generating M-Files to Regenerate Graphs, Publishing M-Files, Distribution Fitting, Nonlinear and Weighted Regression, Color-Intensity Transects of Varved Sediments, and Grain Size Analysis from Microscope Images. The text includes numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. All MATLAB recipes can be easily modified in order to analyse the reader's own data sets.
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