Sinusoidal Regression (Desmos & TI-83)
Definition of sinusoidal regression and how to perform sine regression at Desmos.com or on a TI-83. Link to Desmos file: https://www.desmos.com/calculator/o8qe60dydp 00:00 What is a sinusoidal regression? 01:23 How to do a sin regression in Desmos 04:20 SinReg on the TI-83 graphing
From playlist Regression Analysis
Basic decomposition of a complex sinusoid into a real part consisting of a cosine and an imaginary part consisting of a sine. http://AllSignalProcessing.com for free e-book on frequency in signal processing and much more.
From playlist Background Material
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
From playlist Fourier
Sinusoidal Functions | MIT 18.03SC Differential Equations, Fall 2011
Sinusoidal Functions Instructor: David Shirokoff View the complete course: http://ocw.mit.edu/18-03SCF11 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT 18.03SC Differential Equations, Fall 2011
http://AllSignalProcessing.com for free e-book on frequency in signal processing and much more. Introduction to continuous- and discrete-time sinusoids, relationship between discrete- and continuous-time frequency through sampling, and illustration of using sinusoids to represent more com
From playlist Introduction and Background
1_1 Introductory Notes in Transverse Waves.flv
Introductory notes in transverse waves. Explaining the basics behind the sinusoidal wave patterns of transverse waves.
From playlist Physics - Waves
1_4 Introductory Notes in Transverse Waves.flv
Introductory notes in transverse waves. Explaining the basics behind the sinusoidal wave patterns of transverse waves.
From playlist Physics - Waves
ALiBi | Train Short, Test Long: Attention With Linear Biases Enables Input Length Extrapolation
👨👩👧👦 JOIN OUR DISCORD COMMUNITY: Discord ► https://discord.gg/peBrCpheKE 📢 SUBSCRIBE TO MY MONTHLY AI NEWSLETTER: Substack ► https://aiepiphany.substack.com/ ❤️ Become The AI Epiphany Patreon ❤️ ► https://www.patreon.com/theaiepiphany In this video I cover ALiBi model from the "Train
From playlist Transformers
1_2 Introductory Notes in Transverse Waves.flv
Introductory notes in transverse waves. Explaining the basics behind the sinusoidal wave patterns of transverse waves.
From playlist Physics - Waves
1_3 Introductory Notes in Transverse Waves.flv
Introductory notes in transverse waves. Explaining the basics behind the sinusoidal wave patterns of transverse waves.
From playlist Physics - Waves
Ex: Model Daily Temperatures Using a Trig Function
This video explains how to model daily temperatures using a sinusoidal function given the daily low and high temperature. Site: http://mathispower4u.com Blog: http://mathispower4u.wordpress.com
From playlist Modeling with Trigonometric Functions
Exponential, Step, and Impulse Signals
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Introduction, definition, and examples of exponential, step, and impulse signals in continuous and discrete time.
From playlist Introduction and Background
How do Flies Navigate (Lecture 2) by Larry Abbott
PROGRAM ICTP-ICTS WINTER SCHOOL ON QUANTITATIVE SYSTEMS BIOLOGY (ONLINE) ORGANIZERS: Vijaykumar Krishnamurthy (ICTS-TIFR, India), Venkatesh N. Murthy (Harvard University, USA), Sharad Ramanathan (Harvard University, USA), Sanjay Sane (NCBS-TIFR, India) and Vatsala Thirumalai (NCBS-TIFR,
From playlist ICTP-ICTS Winter School on Quantitative Systems Biology (ONLINE)
This lecture provides an overview of extremum-seeking control (ESC), which is an adaptive equation free method of controlling nonlinear systems. A sinusoidal perturbation is added to the controller, and this perturbation allows the algorithm to locally optimize an objective function. R
From playlist Data-Driven Control with Machine Learning
ALiBi - Train Short, Test Long: Attention with linear biases enables input length extrapolation
#alibi #transformers #attention Transformers are essentially set models that need additional inputs to make sense of sequence data. The most widespread additional inputs are position encodings or position embeddings, which add sequence index information in various forms. However, this has
From playlist Papers Explained
EE102: Introduction to Signals & Systems, Lecture 24
These lectures are from the EE102, the Stanford course on signals and systems, taught by Stephen Boyd in the spring quarter of 1999. More information is available at https://web.stanford.edu/~boyd/ee102/
From playlist EE102: Introduction to Signals & Systems
CS25 I Stanford Seminar - Audio Research: Transformers for Applications in Audio, Speech and Music
Transformers have touched many fields of research and audio and music is no different. This talk will present 3 of my papers as a case study done, on how we can leverage powerfulness of Transformers, with that of representation learning, signal processing and clustering. For the first part
From playlist Stanford Seminars
Parametric vs Nonparametric Spectrum Estimation
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Introduces parametric (model-based) and nonparametric (Fourier-based) approaches to estimation of the power spectrum.
From playlist Estimation and Detection Theory
How This Equation Describes All Waves Around Us (+ the Most Boring Solution) - Parth G Wave Equation
What does it mean to "solve" the Wave Equation? And why is the most boring solution so important? In this video, we will take a look at what is known as the wave equation. In reality, there are a few different equations in physics (even in classical physics) that describe wave behavior, b
From playlist Classical Physics by Parth G
Vibrating string, a simulation made with Excel
The simulation starts with a sinusoid given by the first initial condition u(x,0)=sin(πx/n). The second initial condition is an exact copy, u(x,1)=u(x,0), of the first. The initial velocity, then, is zero (there is of course acceleration). The simulation produces more sinusoids and a perfe
From playlist Physics simulations