Radio frequency propagation model
Log-distance path loss model
The log-distance path loss model is a radio propagation model that predicts the path loss a signal encounters inside a building or densely populated areas over distance. (Wikipedia).
Radio frequency propagation model
The log-distance path loss model is a radio propagation model that predicts the path loss a signal encounters inside a building or densely populated areas over distance. (Wikipedia).
The Logarithm -- limit definition #shorts
Here's a quick derivation of the limit definition for the logarithm. A previous video, https://youtu.be/bPmooEEXU_8 , relied on this definition. You can read about this derivation here: https://medium.com/mathadam/fall-in-love-with-e-all-over-again-2ddc5d03d4cc?sk=8f7111156005f8db169a628a9
From playlist e
Logistic Growth Function and Differential Equations
This calculus video tutorial explains the concept behind the logistic growth model function which describes the limits of population growth. This shows you how to derive the general solution or logistic growth formula starting from a differential equation which describes the population gr
From playlist New Precalculus Video Playlist
Isolating a logarithm and using the power rule to solve
👉 Learn how to solve logarithmic equations. Logarithmic equations are equations with logarithms in them. To solve a logarithmic equation, we first isolate the logarithm part of the equation. After we have isolated the logarithm part of the equation, we then get rid of the logarithm. This i
From playlist Solve Logarithmic Equations
Yann LeCun: "Deep Learning, Graphical Models, Energy-Based Models, Structured Prediction, Pt. 4"
Graduate Summer School 2012: Deep Learning, Feature Learning "Deep Learning, Graphical Models, Energy-Based Models, Structured Prediction, Pt. 4" Yann LeCun, New York University Institute for Pure and Applied Mathematics, UCLA July 13, 2012 For more information: https://www.ipam.ucla.ed
From playlist GSS2012: Deep Learning, Feature Learning
Score estimation with infinite-dimensional exponential families – Dougal Sutherland, UCL
Many problems in science and engineering involve an underlying unknown complex process that depends on a large number of parameters. The goal in many applications is to reconstruct, or learn, the unknown process given some direct or indirect observations. Mathematically, such a problem can
From playlist Approximating high dimensional functions
VQ-GAN | PyTorch Implementation
In this video we are implementing the famous Vector Quantized Generative Adversarial Networks (VQGAN) paper using PyTorch. VQGAN is a generative model for image modeling. It was introduced in Taming Transformers for High-Resolution Image Synthesis. The concept is build upon two stages. The
From playlist Paper Implementations
Fabio Toninelli: A second growth model in the Anisotropic KPZ class
Abstract: Dimer models provide natural models of (2+1)-dimensional random discrete interfaces and of stochastic interface dynamics. I will discuss two examples of such dynamics, a reversible one and a driven one (growth process). In both cases we can prove the convergence of the stochastic
From playlist Jean-Morlet Chair - Khanin/Shlosman - 1st Semester 2017
Distance Vector Routing Algorithm In Computer Networks | DV Routing Algorithm | Simplilearn
In this video on 'Distance Vector Routing', we will understand how the network chooses the best and the smallest path for transmitting data packets over the channel. This task is performed by using the Bellman-Ford Algorithm and designing a proper protocol to follow for smooth transmission
From playlist Networking
Graph Theory: 20. Edge Weighted Shortest Path Problem
This video explains the problem known as the edge-weighted shortest path problem. The next two videos look at an algorithm which provides a solution to the problem. --An introduction to Graph Theory by Dr. Sarada Herke. For quick videos about Math tips and useful facts, check out my othe
From playlist Graph Theory part-4
Solving a logarithmic equation in two different ways
👉 Learn how to solve logarithmic equations. Logarithmic equations are equations with logarithms in them. To solve a logarithmic equation, we first isolate the logarithm part of the equation. After we have isolated the logarithm part of the equation, we then get rid of the logarithm. This i
From playlist Solve Logarithmic Equations
Optimal Transport Methods and Applications to Statistics and... (Lecture 3) by Jose Blanchet
PROGRAM: ADVANCES IN APPLIED PROBABILITY ORGANIZERS: Vivek Borkar, Sandeep Juneja, Kavita Ramanan, Devavrat Shah, and Piyush Srivastava DATE & TIME: 05 August 2019 to 17 August 2019 VENUE: Ramanujan Lecture Hall, ICTS Bangalore Applied probability has seen a revolutionary growth in resear
From playlist Advances in Applied Probability 2019
Learning about PyTorch Lightning and stuff :) pt. 3
❤️ Support the channel ❤️ https://www.youtube.com/channel/UCkzW5JSFwvKRjXABI-UTAkQ/join Paid Courses I recommend for learning (affiliate links, no extra cost for you): ⭐ Machine Learning Specialization https://bit.ly/3hjTBBt ⭐ Deep Learning Specialization https://bit.ly/3YcUkoI 📘 MLOps S
From playlist Streams
Bruce Turkington (DDMCS@Turing): Models that minimize the rate of information loss
Complex models in all areas of science and engineering, and in the social sciences, must be reduced to a relatively small number of variables for practical computation and accurate prediction. In general, it is difficult to identify and parameterize the crucial features that must be incorp
From playlist Data driven modelling of complex systems
Nexus Trimester- Paul Beame (University of Washington) - 1
Branching Programs 2/3 Paul Beame (University of Washington) February 26,2016 Abstract: Branching programs are clean and simple non-uniform models of computation that capture both time and space simultaneously. We present the best methods known for obtaining lower bounds on the size of (l
From playlist Nexus Trimester - 2016 - Fundamental Inequalities and Lower Bounds Theme
Solving a natural logarithmic equation using your calculator
👉 Learn how to solve logarithmic equations. Logarithmic equations are equations with logarithms in them. To solve a logarithmic equation, we first isolate the logarithm part of the equation. After we have isolated the logarithm part of the equation, we then get rid of the logarithm. This i
From playlist Solve Logarithmic Equations
TensorFlow Full Course | Learn TensorFlow in 3 Hours | TensorFlow Tutorial For Beginners | Edureka
** TensorFlow Training (Use Code: YOUTUBE20): https://www.edureka.co/ai-deep-learning-with-tensorflow ** This Edureka TensorFlow Full Course video is a complete guide to Deep Learning using TensorFlow. It covers in-depth knowledge about Deep Learning, Tensorflow & Neural Networks. Below ar
From playlist Deep Learning With TensorFlow Videos
