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GG413: Introduction to Spectral Analysis
 
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University of Hawaii, Dept. of Geology & Geophysics, Garrett Apuzen-Ito, GG413: Geological Data Analysis www.soest.hawaii.edu/GG/FACULTY/ITO/GG413
Views: 16596 Garrett Apuzen-Ito
Time Series Analysis (Georgia Tech) - 5.1.2 - Spectral Analysis - Introduction
 
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Time Series Analysis PLAYLIST: https://tinyurl.com/TimeSeriesAnalysis-GeorgiaTech Unit 5: Other Time Series Methods Part 1: Univariate Time Series Modelling Lesson: 2 - Spectral Analysis - Introduction Notes, Code, Data: https://tinyurl.com/Time-Series-Analysis-NotesData
Views: 252 Bob Trenwith
Spectral analysis
 
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Currell: Scientific Data Analysis. SPSS and Minitab analyses for Figs 7.16 and 7.18 http://ukcatalogue.oup.com/product/9780198712541.do © Oxford University Press
Two Effective Algorithms for Time Series Forecasting
 
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In this talk, Danny Yuan explains intuitively fast Fourier transformation and recurrent neural network. He explores how the concepts play critical roles in time series forecasting. Learn what the tools are, the key concepts associated with them, and why they are useful in time series forecasting. Danny Yuan is a software engineer in Uber. He’s currently working on streaming systems for Uber’s marketplace platform. This video was recorded at QCon.ai 2018: https://bit.ly/2piRtLl For more awesome presentations on innovator and early adopter topics, check InfoQ’s selection of talks from conferences worldwide http://bit.ly/2tm9loz Join a community of over 250 K senior developers by signing up for InfoQ’s weekly Newsletter: https://bit.ly/2wwKVzu
Views: 42777 InfoQ
8. Time Series Analysis I
 
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MIT 18.S096 Topics in Mathematics with Applications in Finance, Fall 2013 View the complete course: http://ocw.mit.edu/18-S096F13 Instructor: Peter Kempthorne This is the first of three lectures introducing the topic of time series analysis, describing stochastic processes by applying regression and stationarity models. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 180469 MIT OpenCourseWare
Spectral Analysis with MATLAB
 
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See what's new in the latest release of MATLAB and Simulink: https://goo.gl/3MdQK1 Download a trial: https://goo.gl/PSa78r MathWorks engineers illustrate techniques of visualizing and analyzing signals across various applications. Using MATLAB and Signal Processing Toolbox functions we show how you can easily perform common signal processing tasks such as data analysis, frequency domain analysis, spectral analysis and time-frequency analysis techniques. This webinar is geared towards scientists / engineers who are not experts in signal processing. Webinar highlights include: A practical introduction to frequency domain analysis. How to use spectral analysis techniques to gain insight into data. Ways to easily carry out signal measurement tasks. View example code from this webinar here. About the Presenter Kirthi Devleker is the product marketing manager for Signal Processing Toolbox at MathWorks. He holds a MSEE degree from San Jose State University
Views: 39497 MATLAB
Time Series Analysis (Georgia Tech) - 5.1.3 - Spectral Analysis - Spectral Density and Covariance Fn
 
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Time Series Analysis PLAYLIST: https://tinyurl.com/TimeSeriesAnalysis-GeorgiaTech Unit 5: Other Time Series Methods Part 1: Univariate Time Series Modelling Lesson: 3 - Spectral Analysis - Spectral Density and Covariance Functions Notes, Code, Data: https://tinyurl.com/Time-Series-Analysis-NotesData
Views: 53 Bob Trenwith
Periodogram Analysis
 
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Paper: Stochastic Processes and Time Series Analysis Module Periodogram Analysis Content Writer: Samopriya Basu/ Sugata Sen Roy
Views: 3916 Vidya-mitra
Spectrum View: A New Way of Performing Multi-Channel Spectrum Analysis on an Oscilloscope
 
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If you're doing mixed frequency/time domain work, Spectrum View makes it easy. Learn how to set up 5 and 6 Series MSOs to display synchronized time and frequency domain views on multiple channels, with the ability to adjust waveform and spectrum controls independently. Read more here: https://www.tek.com/blog/new-approach-frequency-analysis-oscilloscopes-part-1
Views: 234 Tektronix
Graphing a Frequency Spectrum with Matlab
 
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How to use Matlab to compute and graph the frequency spectrum of a sampled time signal. More instructional engineering videos can be found at http://www.engineeringvideos.org. This video is licensed under the Creative Commons BY-SA license http://creativecommons.org/licenses/by-sa/3.0/us/.
Views: 125613 Darryl Morrell
17.11: Sound Visualization: Frequency Analysis with FFT - p5.js Sound Tutorial
 
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In this "p5.js Sound Tutorial" video, I use the p5.FFT object to analyze the frequencies (spectrum array) of a sound file. I create a "graphic equalizer" like visualization. Support this channel on Patreon: https://patreon.com/codingtrain Send me your questions and coding challenges! Contact: https://twitter.com/shiffman p5.js sound library reference: https://p5js.org/reference/#/libraries/p5.sound p5.FFT object reference: https://p5js.org/reference/#/p5.FFT Kristian Pedersen's this.dot song: https://soundcloud.com/kristianpedersen/this-dot-feat-daniel-shiffman Source Code for the Video Lessons: https://github.com/CodingTrain/Rainbow-Code p5.js: https://p5js.org/ Processing: https://processing.org For More Sound in p5.js videos: https://www.youtube.com/playlist?list=PLRqwX-V7Uu6aFcVjlDAkkGIixw70s7jpW Help us caption & translate this video! http://amara.org/v/YIOn/
Views: 101549 The Coding Train
How to do Spectral analysis or FFT of Signal in Python??
 
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This tutorial video teaches about signal FFT spectrum analysis in Python. This video teaches about the concept with the help of suitable examples. We also provide online training, help in technical assignments and do freelance projects based on Python, Matlab, Labview, Embedded Systems, Linux, Machine Learning, Data Science etc. For more details and to get the source code of this video, Please visit us at: www.jcbrolabs.org
Views: 225 sachin sharma
Spectrum Monitoring with a Real-Time Spectrum Analyzer
 
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With RIGOL's RSA5000 series spectrum analyzers users are able to first identify signals of interests in the swept spectrum mode and then further isolate and view the signals in real-time mode. Learn more about Real-Time Spectrum Analysis and RSA5000 series: https://www.rigolna.com/real-time/ RSA5000 series product page: https://www.rigolna.com/products/spectrum-analyzers/rsa5000/ RSA3000 series product page: https://www.rigolna.com/products/spectrum-analyzers/rsa3000/
Views: 1577 RigolTech
09 Spectral analysis
 
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Versión en Español: https://www.youtube.com/watch?v=mF8jf0JibcE&index=9&list=PLc6BlWWbxqOK1d85kjXGlzO8FIlVX4ZAw Awesome Audio channel link: www.youtube.com/AwesomeAudioChannel References: http://wallpaperspixel.com/computers/mac-cpu-wallpaper/attachment/mac-cpu-wallpaper-2/ http://www.versci.com/fft/index.html http://www.voxengo.com/product/span/ https://www.thinglink.com/scene/670610196824850433 http://sourceforge.net/projects/ltfat/
Views: 2112 AwesomeAudioChannel
Introduction of the RSA3000 series Real-Time Spectrum Analyzers
 
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The RSA3000 series combines real time capture and swept capture capabilities with a flexible form factor allowing an engineer to select their preferred test techniques, interface, and use modes. With the frequency ranges of 3 GHz and 4.5 GHz, the RSA3000 is ideal for analysis of components and complex signals in EMI, IoT, Wi-Fi, and a variety of other wireless communication applications. Learn more about Real-Time Spectrum Analysis and RSA3000 series: https://www.rigolna.com/real-time/ RSA3000 series product page: https://www.rigolna.com/products/spectrum-analyzers/rsa3000/
Views: 595 RigolTech
Real-time Signal Processing and Analysis on Measurement Data
 
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See more videos- http://bit.ly/aMdhSC Add a low-pass filter and frequency domain analysis to measurement data, while it's continuously being streamed from a USB data acquisition device.
Views: 126505 niglobal
The Discrete Fourier Transform: Sampling the DTFT
 
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http://AllSignalProcessing.com for free e-book on frequency relationships and more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files.
Views: 94047 Barry Van Veen
Broad overview of EEG data analysis analysis
 
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This lecture is a very broad introduction to the most commonly used data analyses in cognitive electrophysiology. There is no math, no Matlab, and no data to download. For more information about MATLAB programming: https://www.udemy.com/matlab-programming-mxc/?couponCode=MXC-MATLAB10 For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/
Views: 14041 Mike X Cohen
Plotting Frequency Spectrum using Matlab
 
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Outlines the key points to understanding the matlab code which demonstrates various ways of visualising the frequency content of a signal at http://dadorran.wordpress.com/2014/02/17/plot_freq_spectrum/. This code is published in a more visually friendly way at http://dadorran.wordpress.com/2014/02/20/plotting-frequency-spectrum-using-matlab/
Views: 194455 David Dorran
Time Domain vs. Frequency Domain, What’s the Difference? – What the RF (S01E02)
 
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Learn the difference between the time and frequency domains Click to subscribe: http://bit.ly/Labs_Sub Learn more in the Spectrum Analysis Basics application note ↓ ► http://bit.ly/SpecAnBasics ◄ Like our Facebook page for more exciting stuff: https://www.facebook.com/keysightrf Check out our blog: http://bit.ly/RFTestBlog Learn more about using oscilloscopes: http://oscilloscopelearningcenter.com Check out the EEs Talk Tech electrical engineering podcast: https://eestalktech.com Like our digital counterpart’s Facebook page: https://www.facebook.com/keysightbench/ In this episode of What the RF (WTRF) Nick goes into detail on the difference between the time domain and frequency domain and demonstrates both on an oscilloscope and signal analyzer respectively. What exactly is the difference between the time domain and frequency domain? And what about the frequency domain tells us more about our signal? In this video we have the same signal going to an oscilloscope and a signal analyzer, both being tools to visualize electrical signals in the time and frequency domain respectively. Typically the higher the frequency, the more waves we see in the same span on our oscilloscope. In the time-domain, signals appear as sinusoidal waves and in the frequency-domain they appear as distinct impulses. But why do we care to use a signal analyzer? In a perfect world we would see the undistorted sinusoidal waveform like we would see on an oscilloscope, but we don’t live in a perfect world. When dealing with various devices it’s often you see a not so perfect, distorted sine wave with many ripples. You can say that a real-world signal can be represented as a sum of different sinusoid signals, or rather different frequencies. Now let’s say you’re designing a product and your product can only operate in a specified bandwidth and can’t be emitting in other bandwidths. Then you must determine at what other frequencies do the other signals exist that are corrupting the signal you want from your device And that’s where signal analyzers come in – they help separate and display this combination of different sinusoid signals into their distinct frequency components … so that if you were expecting your device to operate at a certain frequency you can see all the other frequencies that are messing with your device. And once that’s figured out you can use a band-pass filter to tune out those annoying extra signals you weren’t expecting – hence the benefit of seeing signals in the frequency domain! Tune in for future What The RF (WTRF) episodes covering more spectrum analyzer capabilities and fundamental measurements to see how you can test more efficiently! The signal analyzer we used: http://bit.ly/MXASignalAnalyzer (The Keysight X-Series MXA Signal Analyzer) The X-Series signal analyzers allow you to visualize across the spectrum to see known and unknown signals. Choose from frequencies of 3 Hz – 110 GHz and 1 MHz – 1 GHz analysis bandwidth. What the RF is hosted by Nick Ben. The video series covers when and how to use analyzers to make various RF measurements. You’ll gain familiarity with features that will help you save time in your measurement, further your analysis, and deepen your insight. #RF #SpectrumAnalyzer #SignalAnalyzer #TimeDomain #FrequencyDomain #timevsfrequencydomain #electricalengineering #rfengineering #fourier #electronics
Views: 22181 Keysight Labs
Singular Spectrum Analysis A New Tool in Time Series Analysis Paperback
 
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Singular Spectrum Analysis A New Tool in Time Series Analysis Paperback.cbooks.club
Views: 827 Lois Bennett
The Power Spectral Density
 
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http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Representation of wide sense stationary random processes in the frequency domain - the power spectral density or power spectrum is the DTFT of the autocorrelation sequence for a random process and describes the contribution of each frequency to the overall variance of the process.
Views: 118855 Barry Van Veen
Fourier Transform, Fourier Series, and frequency spectrum
 
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Fourier Series and Fourier Transform with easy to understand 3D animations.
View Signals in the Time Domain on a Spectrum Analyzer
 
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Spectrum analyzers are most frequently used to measure and observe signals in the frequency domain. But another useful feature can be to configure the analyzer for time domain measurements. DSA800 series product page: https://www.rigolna.com/products/spectrum-analyzers/dsa800/ DSA700 series product page: https://www.rigolna.com/products/spectrum-analyzers/dsa700/
Views: 1020 RigolTech
Using Python for real-time signal analysis (Mohammad Farhan)
 
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PyCon Canada 2015: https://2015.pycon.ca/en/schedule/50/ Talk Description: The main subject of this talk is how Python can be used as an alternative to the more commonly used high-level languages used in the scientific data analysis industry. This talk will focus on PyRF, an open-source library developed by ThinkRF, and how it has been used to provide the same functionality in terms of instrumentation control, data acquisition, digital signal processing, automated testing, production testing, as well as application development.
Views: 28783 PyCon Canada
Let's Build an Audio Spectrum Analyzer in Python! (pt. 1) the waveform viewer.
 
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In this series, we'll build an audio spectrum analyzer using pyaudio and matplotlib. In part 1, we'll go step by step on how to stream audio data from a microphone into python using pyaudio. We'll then use matplotlib in an optimized way so that we can display the audio wavefrom in real time! (sorry about the clicks and pops!) code github: https://github.com/markjay4k/Audio-Spectrum-Analyzer-in-Python pyaudio docs: https://people.csail.mit.edu/hubert/pyaudio/docs/ how to speed up matplotlib: http://bastibe.de/2013-05-30-speeding-up-matplotlib.html
Views: 48148 Mark Jay
Bootcamp no. 10 - Discrete Fourier Transform functions in Excel
 
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In this video, we will demonstrate the use of the Discrete Fourier Transform to transform a sample data into its frequency components and to re-construct it using the inverse DFT. For our example, we'll use a sample data simulated from ARMA(2,1) process. For more information, please visit http://www.spiderfinancial.com/support/documentation/numxl/reference-manual/spectral-analysis
Views: 62112 NumXL
Power Spectral Density Plot using MATLAB | Uniformedia 2017
 
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Power spectral density function (PSD) shows the strength of the variations(energy) as a function of frequency. In other words, it shows at which frequencies variations are strong and at which frequencies variations are weak. The unit of PSD is energy (variance) per frequency(width) and you can obtain energy within a specific frequency range by integrating PSD within that frequency range. For more informations check: http://www.cygres.com/OcnPageE/Glosry/SpecE.html
Views: 13745 Uniformedia
FFT basic concepts
 
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Basic concepts related to the FFT (Fast Fourier Transform) including sampling interval, sampling frequency, bidirectional bandwidth, array indexing, frequency bin width, and Nyquist frequency.
Views: 185946 NTS
Lecture - 34 Introduction to Spectral Analysis
 
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Lecture Series on Probability and Random Variables by Prof. M.Chakraborty, Dept. of Electronics and Electrical Engineering,I.I.T.,Kharagpur.For more Courses visit http://nptel.iitm.ac.in
Views: 23822 nptelhrd
Multitaper
 
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The final time-frequency analysis method shown here is the multitaper method. It is an extention of the STFFT that can be useful in low-SNR situations. This video uses the following MATLAB files: http://mikexcohen.com/lecturelets/multitaper/multitaper.m http://mikexcohen.com/lecturelets/sampleEEGdata.mat For more online courses about programming, data analysis, linear algebra, and statistics, see http://sincxpress.com/
Views: 1911 Mike X Cohen
RSA600 Real Time Spectrum Analyzer
 
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Developed to enable design teams to quickly and easily perform lab tasks, from EMI sniffing to IoT wireless standards compliance, the RSA600 series is the essential lab tool for RF analysis.
Views: 19439 Tektronix
Significance of Time domain and Frequency domain
 
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This video gives a brief idea about the need for Time domain and frequency domain... This video may help you understand the frequency domain and appreciate it's importance..
Views: 113299 Suraj Hebbar
Introduction of the RSA5000 series Real-Time Spectrum Analyzers
 
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The RSA5000 series combines real time capture and swept capture capabilities with a flexible form factor allowing an engineer to select their preferred test techniques, interface, and use modes. With the frequency ranges of 3.2 GHz and 6.5 GHz, the RSA5000 is ideal for analysis of components and complex signals in EMI, IoT, Wi-Fi, cellular, and a variety of other wireless communication applications. Learn more about Real-Time Spectrum Analysis and RSA5000 series: https://www.rigolna.com/real-time/ RSA5000 series product page: https://www.rigolna.com/products/spectrum-analyzers/rsa5000/
Views: 1939 RigolTech
Simple and Easy Tutorial on FFT Fast Fourier Transform Matlab Part 1
 
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This simple tutorial video is about using FFT function in Matlab. watch the second parts here https://youtu.be/HiIvbIl95lE
Views: 164474 asraf mohamed
BB60C Real time Spectrum Analysis Demo
 
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A Signal Hound BB60C is used to discover and analyze a Bluetooth signal. View full details at https://signalhound.com/products/bb60c/, purchase for only $2879 USD.
Views: 8867 Signal Hound
Fourier Series Part 1
 
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Joseph Fourier developed a method for modeling any function with a combination of sine and cosine functions. You can graph this with your calculator easily and watch the modeling in action. Make sure you're in radian mode and let c=1: f(x) = 4/(pi)*sin(x) + 4/(3pi)*sin(3x) + 4/(5pi)*sin(5x) + 4/(7pi)*sin(7x) + 4/(9pi)*sin(9x) + 4/(11pi)*sin(11x)
Views: 924787 Saul Rémi
Signal Analysis Made Easy
 
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Download a trial: https://goo.gl/PSa78r See what's new in the latest release of MATLAB and Simulink: https://goo.gl/3MdQK1 In this webinar, we will showcase how easy it is to perform Signal Analysis tasks in MATLAB. The presentation is geared towards users who want to analyze signal data regardless of their signal processing expertise. You will learn common signal analysis techniques such as visualizing and pre-processing the signal, filtering, identifying and measuring relevant features. We will use signals from variety of application areas and demonstrate how to : Import and visualize signal data Pre-process and filter signals to enhance the quality of the signal Visualize the signal in time domain and frequency domains Analyze and measure trends, peaks, and other characteristic features of the signal Create a MATLAB app to package the analysis into a single file and distribute to others
Views: 66344 MATLAB
Let's Build an Audio Spectrum Analyzer in Python! (pt. 2) the spectrum viewer
 
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In this series, we'll build an audio spectrum analyzer using pyaudio and matplotlib. In part 2, we'll use scipy.fftpack to compute the FFT and display the audio spectrum in real time. notebook (Github): https://github.com/markjay4k/Audio-Spectrum-Analyzer-in-Python scipy docs: https://docs.scipy.org/doc/scipy-0.14.0/reference/tutorial/fftpack.html Fourier Series Videos: https://www.youtube.com/watch?v=rozd8MwQYYs&list=PLX-LrBk6h3wQczbulbyeg7gFr1_T1YN4c
Views: 15379 Mark Jay
fft with excel
 
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Calculate fft with excel
Views: 68151 Mike Holden
The Fourier Transform- Part I
 
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A short tutorial video on how the Fourier Transform works. The video is designed for those who know what a Fourier Transform is but need to understand at a basic level how it converts time domain signals into the frequency domain.
Views: 443165 kridnix
Lecture 6A:Frequency Domain Analysis, Power Spectrum & Multi-Taper Estimate, Dr. Wim van Drongelen
 
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Lecture 6 (taught by grad students Albert Wildeman, Tahra Eissa) Frequency Domain Analysis: The Power Spectrum and Multi-Taper Estimate (CH 7 and Handout) Book: Signal Processing for Neuroscientists by Wim van Drongelen Course: Modeling and Signal Analysis for Neuroscientists
Views: 2178 epilepsylab uchicago
Coherence and the Cross Spectrum
 
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http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Coherence and the cross spectrum describe the relationship between two random signals in the frequency domain based on their second order statistics (auto and cross correlation). The cross spectrum is the DTFT of the cross correlation between the two signals and the magnitude squared coherence is the magnitude squared of the cross spectrum normalized to by the power spectrum of the signals. The magnitude squared coherence is unity for signals that are related through a linear time invariant system.
Views: 20546 Barry Van Veen
Introduction into Real Time Spectrum Analysis: Rigol RSA5000 Series Spectrum Analyzers
 
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Learn More about the RSA5000 Series: https://www.tequipment.net/Rigol/RSA5032/Spectrum-Analyzers/?ref=youtube This video gives an introduction to the real-time analysis capabilities of the Rigol RSA5000 Series spectrum analyzers. These are Rigol's first ever real-time spectrum analyzers.
Views: 123 TEquipment.NET
Sampling Signals (3/13) - Fourier Transform of an Impulse Sampled Signal
 
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http://adampanagos.org We investigate impulse sampling in the frequency domain, i.e. we derive an expression for the Fourier Transform (FT) of a signal that has been impulse sampled. If x(t) is the continuous-time signal with corresponding FT X(w), the impulse sampled version of x(t) has a FT that consists of an infinite collection of X(w) shifted up and down the frequency axis. Each shifted version of X(w) occurs at an integer multiple of the sampling frequency ws. If you enjoyed my videos please "Like", "Subscribe", and visit http://adampanagos.org to setup your member account to get access to downloadable slides, Matlab code, an exam archive with solutions, and exclusive members-only videos. Thanks for watching!
Views: 50245 Adam Panagos
Benefits of Real Time Spectrum Analysis: Rigol RSA5000 Series Spectrum Analyzers
 
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Learn More about the RSA5000 Series: https://www.tequipment.net/Rigol/RSA5032/Spectrum-Analyzers/?ref=youtube This video goes over the key points and benefits of using real-time spectrum analysis on Rigol RSA5000 Series spectrum analyzers. These are Rigol's first ever real-time spectrum analyzers.
Views: 78 TEquipment.NET
Spectrum of a Sine Wave - MATLAB Tutorial for Beginners 2017
 
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Spectrum of a Sinusoidal Wave - MATLAB Tutorial for Beginners 2017 A sine wave consists of a single frequency only, and its spectrum is a single point. Theoretically, a sine wave exists over infinite time and never changes. The mathematical transform that converts the time domain waveform into the frequency domain is called the Fourier transform, and it compresses all the information in the sine wave over infinite time into one point.
Views: 9091 Uniformedia

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