MiLABEx vs Stochastic Signal Processing Uso e estatísticas

MiLABEx™, Fourier Education’s mobile data analysis app for iOS devices, is based on Fourier’s award-winning MultiLab™ analysis software. MiLABEx unlocks a world of scientific experiments for teachers and students alike. Supported devices: einstein™ Tablet+ & einstein™ Tablet einstein™ LabMate+ & einstein™ LabMate™ Languages: English (en), Czech (cs), German (de), Spanish (es), French (fr), Hebrew (he/iw), Italian (it), Japanese (ja), Lithuanian (lt), Polish (pl), Portuguese (pt), Russian (ru), Slovak (sk), Ukrainian (uk), Chinese simplified (zh-rCN) ALBERT EINSTEIN and EINSTEIN are either trademarks or registered trademarks of The Hebrew University of Jerusalem. Represented exclusively by GreenLight. Official licensed merchandise. Website: einstein.biz © 2015 Fourier Systems Ltd. All rights reserved. Fourier Systems Ltd. logos and all other Fourier product or service names are registered trademarks or trademarks of Fourier Systems. All other registered trademarks or trademarks belong to their respective companies. Features: Intuitive and simple interface Professional data analysis tool Multiple data display modes: graphs, tables, meters and map Drag & drop window displays Real-time data measurements via built-in and external sensors Supports over 65 Fourier sensors Supports GPS for location based experiments Experiment note-taking feature Export and Share options ALBERT EINSTEIN and EINSTEIN are either trademarks or registered trademarks of The Hebrew University of Jerusalem. Represented exclusively by GreenLight. Official licensed merchandise. Website: einstein.biz © 2014 Fourier Systems Ltd. All rights reserved. Fourier Systems Ltd. logos and all other Fourier product or service names are registered trademarks or trademarks of Fourier Systems. All other registered trademarks or trademarks belong to their respective companies
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Speech, music, seismic vibrations, oil prices, and climate measurements are all examples of stochastic (random) signals. In this textbook—intended for individuals with prior training in introductory signal processing and introductory probability theory—we develop techniques to process such signals to extract useful information. We present case studies ranging from music to photographic images to oil prices to climate data to the motion of individual biomolecules. This textbook, as an interactive textbook ("iBook"), makes use of your device's ability to display dynamic information through films and animations and to hear the results of the techniques applied to music. At the end of every chapter there are homework problems ranging from easy to "olympic". A new and exciting aspect is that we make use of your device's interactive capabilities to offer 59 laboratory experiments in signal processing. The experiments use the camera, the microphone, the speakers, and the graphical user interface. These experiments are not simulations; they are examples of real digital processing of signals in your device. In this time of at-home and online learning, this is the way to learn signal processing through study and experimentation.
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MiLABEx VS.
Stochastic Signal Processing

19ezembro d, 2024