Classical control theory | Linear algebra | Signal processing | Application-specific graphs
A signal-flow graph or signal-flowgraph (SFG), invented by Claude Shannon, but often called a Mason graph after Samuel Jefferson Mason who coined the term, is a specialized flow graph, a directed graph in which nodes represent system variables, and branches (edges, arcs, or arrows) represent functional connections between pairs of nodes. Thus, signal-flow graph theory builds on that of directed graphs (also called digraphs), which includes as well that of oriented graphs. This mathematical theory of digraphs exists, of course, quite apart from its applications. SFGs are most commonly used to represent signal flow in a physical system and its controller(s), forming a cyber-physical system. Among their other uses are the representation of signal flow in various electronic networks and amplifiers, digital filters, state-variable filters and some other types of analog filters. In nearly all literature, a signal-flow graph is associated with a set of linear equations. (Wikipedia).
Signal Flow Graph Example Part 1
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From playlist RF Amplifier Design
Signal Flow Graph Introduction
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From playlist RF Amplifier Design
Notation and Basic Signal Properties
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. Signals as functions, discrete- and continuous-time signals, sampling, images, periodic signals, displayi
From playlist Introduction and Background
Introduction to Signal Processing
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. Introductory overview of the field of signal processing: signals, signal processing and applications, phi
From playlist Introduction and Background
Signal Flow Graph Example Part 2
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From playlist RF Amplifier Design
Introduction to Random Signal Representation
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Introduction to the concept of a random signal, then review of probability density functions, mean, and variance for scalar quantities.
From playlist Random Signal Characterization
Characterization of Random, Multivariate Signals
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Multivariable (vector) probability density function representations, including the multivariate Gaussian density. The covariance matrix and in
From playlist Random Signal Characterization
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
Graph Data Structure 1. Terminology and Representation (algorithms)
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with graphs, and describes how a graph can be represented programmatically by means of adjacency lists or an adjacency matrix.
From playlist Data Structures
Lec 11 | MIT RES.6-008 Digital Signal Processing, 1975
Lecture 11: Representation of linear digital networks Instructor: Alan V. Oppenheim View the complete course: http://ocw.mit.edu/RES6-008S11 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT RES.6-008 Digital Signal Processing, 1975
AMMI 2022 Course "Geometric Deep Learning" - Seminar 1 (Physics-based GNNs) - Francesco Di Giovanni
Video recording of the course "Geometric Deep Learning" taught in the African Master in Machine Intelligence in July 2022 Seminar 1 - Graph neural networks through the lens of multi-particle dynamics and gradient flows - Francesco Di Giovanni (Twitter) Slides: https://www.dropbox.com/s/
From playlist AMMI Geometric Deep Learning Course - Second Edition (2022)
Deep Learning Live - 3 | TensorFlow Tutorial | Deep Learning Using TensorFlow Training | Edureka
🔥Edureka TensorFlow Training - https://www.edureka.co/ai-deep-learning-with-tensorflow This Edureka TensorFlow Tutorial video (Blog: https://goo.gl/4zxMfU) will help you in understanding various important basics of TensorFlow. It also includes a use-case in which we will create a model tha
From playlist Edureka Live Classes 2020
GRCon20 - Ultra-cheap SDR Digital Television Transmission: ISDB-T with an osmo-fl2k and an RTL-SDR
Presented by Federico Larroca, Pablo Flores Guridi, David Artenstein, Lucas Inglés and Gastón Morales at GNU Radio Conference 2020 https://gnuradio.org/grcon20 We present the implementation in GNU Radio of an ISDB-T transmitter, the digital television standard used in most South American
From playlist GRCon 2020
Lecture 9: GNNs as Dynamic Systems - Francesco Di Giovanni
Video recording of the First Italian School on Geometric Deep Learning held in Pescara in July 2022. Slides: https://www.sci.unich.it/geodeep2022/slides/GRAFF_presentation%20(17).pdf
From playlist First Italian School on Geometric Deep Learning - Pescara 2022
GRCon19 - Managing Latency in Continuous GNU Radio Flowgraphs by Matt Ettus
Managing Latency in Continuous GNU Radio Flowgraphs by Matt Ettus
From playlist GRCon 2019
Motion Graphs (4 of 8) Velocity vs. Time Graph Part 1
Shows how to read a velocity vs. time graph including direction of motion, velocity, acceleration and how to calculate the acceleration. You can see a listing of all my videos at my website, http://www.stepbystepscience.com Motion graphs are an excellent way to get an understanding of an
From playlist Motion Graphs; Position and Velocity vs. Time
GRCon19 - gr-satellites: a collection of decoders for Amateur satellites by Daniel Estévez
gr-satellites: a collection of decoders for Amateur satellites by Daniel Estévez gr-satellites is an OOT module encompassing a collection of telemetry decoders that supports nearly 40 different Amateur satellites. This open-source project started in 2015 with the goal of providing telemet
From playlist GRCon 2019