For data compression, Signaling compression, or SigComp, is a compression method designed especially for compression of text-based communication data as SIP or RTSP. SigComp had originally been defined in RFC 3320 and was later updated with RFC 4896. A Negative Acknowledgement Mechanism for Signaling Compression is defined in RFC 4077. The SigComp work is performed in the ROHC working group in the transport area of the IETF. (Wikipedia).
A discrete signal has to be reconstructed to get back into the continuous domain.
From playlist Discrete
Physics demonstrations. Polarisation of microwaves
This video shows how you can use a microwave transmitter and receiver to investigate the polarisation of microwaves. Plane polarised waves are emitted by the transmitter and If you measure the angle of the filter and record the intensity at the receiver you can then show.
From playlist WAVES
Determining Signal Similarities
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Find a signal of interest within another signal, and align signals by determining the delay between them using Signal Processing Toolbox™. For more on Signal Processing To
From playlist Signal Processing and Communications
Get a Free Trial: https://goo.gl/C2Y9A5 Get Pricing Info: https://goo.gl/kDvGHt Ready to Buy: https://goo.gl/vsIeA5 Determine the period of a signal by measuring the distance between the peaks, and find peaks in a noisy signal using Signal Processing Toolbox™. For more on Signal Process
From playlist Signal Processing and Communications
Introduction to Frequency Selective Filtering
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. Separation of signals based on frequency content using lowpass, highpass, bandpass, etc filters. Filter g
From playlist Introduction to Filter Design
Just talking about compression and stuff -- Watch live at https://www.twitch.tv/simuleios
From playlist Misc
5G Explained: Synchronization Signal Blocks in 5G NR
View the full playlist here: https://www.youtube.com/playlist?list=PLn8PRpmsu08rCL-Ejn25HMX6M6o7QjJoe In this video, you’ll learn about the synchronization signal block (SSB) in 5G New Radio (NR). The SSB is comprised of the primary and secondary synchronization signals (PSS and SSS) as we
From playlist 5G Explained
Measurements vs. Bits: Compressed Sensors and Info Theory
October 18, 2006 lecture by Dror Baron for the Stanford University Computer Systems Colloquium (EE 380). Dror Baron discusses the numerous rich insights information theory has to offer Compressed Sensing (CS), an emerging field based on the revelation that optimization routines can reco
From playlist Course | Computer Systems Laboratory Colloquium (2006-2007)
A Compressed Overview of Sparsity
This talk presents a high level overview of compressed sensing, especially as it relates to engineering applied mathematics. We provide context for sparsity and compression, followed by good rules of thumb and key ingredients to apply compressed sensing.
From playlist Research Abstracts from Brunton Lab
The Unreasonable Effectiveness of JPEG: A Signal Processing Approach
Visit https://brilliant.org/Reducible/ to get started learning STEM for free, and the first 200 people will get 20% off their annual premium subscription. Chapters: 00:00 Introducing JPEG and RGB Representation 2:15 Lossy Compression 3:41 What information can we get rid of? 4:36 Introduc
From playlist Fourier
Structured Regularization Summer School - A.Hansen - 1/4 - 19/06/2017
Anders Hansen (Cambridge) Lectures 1 and 2: Compressed Sensing: Structure and Imaging Abstract: The above heading is the title of a new book to be published by Cambridge University Press. In these lectures I will cover some of the main issues discussed in this monograph/textbook. In par
From playlist Structured Regularization Summer School - 19-22/06/2017
Shannon Nyquist Sampling Theorem
Follow on Twitter: @eigensteve Brunton's website: https://eigensteve.com This video discusses the famous Shannon-Nyquist sampling theorem, which discusses limits on signal reconstruction given how fast it is sampled and the frequency content of the signal. For original papers: Shannon
From playlist Sparsity and Compression [Data-Driven Science and Engineering]
31. Change of Basis; Image Compression
MIT 18.06 Linear Algebra, Spring 2005 Instructor: Gilbert Strang View the complete course: http://ocw.mit.edu/18-06S05 YouTube Playlist: https://www.youtube.com/playlist?list=PLE7DDD91010BC51F8 31. Change of Basis; Image Compression License: Creative Commons BY-NC-SA More information at
From playlist MIT 18.06 Linear Algebra, Spring 2005
Laurent Jacques/Valerio Cambareri: Small width, low distortions: quantized random projections of...
Laurent Jacques / Valerio Cambareri: Small width, low distortions: quantized random projections of low-complexity signal sets Abstract: Compressed sensing theory (CS) shows that a "signal" can be reconstructed from a few linear, and most often random, observations. Interestingly, this rec
From playlist HIM Lectures: Trimester Program "Mathematics of Signal Processing"
Beating Nyquist with Compressed Sensing
This video shows how it is possible to beat the Nyquist sampling rate with compressed sensing (code in Matlab). Book Website: http://databookuw.com Book PDF: http://databookuw.com/databook.pdf These lectures follow Chapter 3 from: "Data-Driven Science and Engineering: Machine Learning,
From playlist Sparsity and Compression [Data-Driven Science and Engineering]
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Frequency domain analysis of upsampling a discrete-time signal (increasing the effective sampling rate) by inserting zeros followed by lowpass filte
From playlist Sampling and Reconstruction of Signals
Where have I heard that song? For us humans, it is pretty easy to recognize a recording. However, to a machine, two signals that sound the same could look totally different! In this talk, Carlo Giacometti uses the Wolfram Language to understand and explore different techniques to identify
From playlist Wolfram Technology Conference 2020
Telecommunications - A Level Physics
A description of telecommunications: AM and FM; use of carrier waves; analog and digital signals; broadcast options; satellite transmission; gain and attenuation; PSTN; mobile/cell phones and networks.
From playlist A Level Physics Revision
Emmanuel Candès: Wavelets, sparsity and its consequences
Abstract: Soon after they were introduced, it was realized that wavelets offered representations of signals and images of interest that are far more sparse than those offered by more classical representations; for instance, Fourier series. Owing to their increased spatial localization at f
From playlist Abel Lectures