A random stimulus is any class of creativity techniques that explores randomization. Most of their names start with the word "random", such as random word, random heuristic, random picture and random sound. In each random creativity technique, the user is presented with a random stimulus and explores associations that could trigger novel ideas. The power of random stimulus is that it can lead you to explore useful associations that would not emerge intentionally. (Wikipedia).
Random Processes and Stationarity
http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Introduction to describing random processes using first and second moments (mean and autocorrelation/autocovariance). Definition of a stationa
From playlist Random Signal Characterization
Statistics: Ch 5 Discrete Random Variable (1 of 27) What is a Random Variable?
Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn a random variable is a variable which represents the outcome of a trial, an experiment, or an event. It is a specific n
From playlist STATISTICS CH 5 DISCRETE RANDOM VARIABLE
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
The Most Powerful Tool Based Entirely On Randomness
We see the effects of randomness all around us on a day to day basis. In this video we’ll be discussing a couple of different techniques that scientists use to understand randomness, as well as how we can harness its power. Basically, we'll study the mathematics of randomness. The branch
From playlist Classical Physics by Parth G
Fixed Effects and Random Effects
Brief overview in plain English of the differences between the types of effects. Problems with each model and how to overcome them.
From playlist Experimental Design
9: Receptive Fields - Intro to Neural Computation
MIT 9.40 Introduction to Neural Computation, Spring 2018 Instructor: Michale Fee View the complete course: https://ocw.mit.edu/9-40S18 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP61I4aI5T6OaFfRK2gihjiMm Covers how to mathematically describe a neural response, spatia
From playlist MIT 9.40 Introduction to Neural Computation, Spring 2018
This lesson introduces the different sample methods when conducting a poll or survey. Site: http://mathispower4u.com
From playlist Introduction to Statistics
Neural Coding and Adaptation (Lecture 1) by Adrienne Fairhall
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)
10: Time Series - Intro to Neural Computation
MIT 9.40 Introduction to Neural Computation, Spring 2018 Instructor: Michale Fee View the complete course: https://ocw.mit.edu/9-40S18 YouTube Playlist: https://www.youtube.com/playlist?list=PLUl4u3cNGP61I4aI5T6OaFfRK2gihjiMm Covers the Poisson Process, spike train variability, convolutio
From playlist MIT 9.40 Introduction to Neural Computation, Spring 2018
Taxes and Kineses | Revision for Biology A-Level and IB
I want to help you achieve the grades you (and I) know you are capable of; these grades are the stepping stone to your future. Even if you don't want to study science or maths further, the grades you get now will open doors in the future. Tutoring - We can match you with an experienced t
From playlist AQA A-Level Biology | Ultimate Revision Playlist
Essentials of Neuroscience with MATLAB: Module 1-4 (spikes)
The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization. This vide
From playlist Essentials of neuroscience with MATLAB
Randomness Quiz - Applied Cryptography
This video is part of an online course, Applied Cryptography. Check out the course here: https://www.udacity.com/course/cs387.
From playlist Applied Cryptography
Operant conditioning: Innate vs learned behaviors | Behavior | MCAT | Khan Academy
Created by Jeffrey Walsh. Watch the next lesson: https://www.khanacademy.org/test-prep/mcat/behavior/learning-slug/v/operant-conditioning-escape-and-avoidance-learning?utm_source=YT&utm_medium=Desc&utm_campaign=mcat Missed the previous lesson? https://www.khanacademy.org/test-prep/mcat/b
From playlist Behavior | MCAT | Khan Academy
Lecture 08: The Neuronal Underpinnings of Attention
Lecture 8 corresponds to Chapter 10 of "The Quest for Consciousness - A Neurobiological Approach," by Christof Koch. Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND). To learn more about th
From playlist The Neuronal Basis of Consciousness Course - CNS/Bi/Psy 120
Thomas Serre: "Deep Learning in the Visual Cortex, Pt. 2"
Graduate Summer School 2012: Deep Learning, Feature Learning "Deep Learning in the Visual Cortex, Pt. 2" Thomas Serre, Brown University Institute for Pure and Applied Mathematics, UCLA July 25, 2012 For more information: https://www.ipam.ucla.edu/programs/summer-schools/graduate-summer-
From playlist GSS2012: Deep Learning, Feature Learning
Nikolaus Kriegskorte - Controversial stimuli: experiments to adjudicate computational hypotheses
Recorded 13 January 2023. Nikolaus Kriegeskorte of Columbia University presents "Controversial stimuli: Optimizing experiments to adjudicate among computational hypotheses" at IPAM's Explainable AI for the Sciences: Towards Novel Insights Workshop. Learn more online at: http://www.ipam.ucl
From playlist 2023 Explainable AI for the Sciences: Towards Novel Insights
(PP 3.1) Random Variables - Definition and CDF
(0:00) Intuitive examples. (1:25) Definition of a random variable. (6:10) CDF of a random variable. (8:28) Distribution of a random variable. A playlist of the Probability Primer series is available here: http://www.youtube.com/view_play_list?p=17567A1A3F5DB5E4
From playlist Probability Theory