Space-time adaptive processing

Review of Linear Time Invariant Systems

http://AllSignalProcessing.com for more great signal-processing content: ad-free videos, concept/screenshot files, quizzes, MATLAB and data files. Review: systems, linear systems, time invariant systems, impulse response and convolution, linear constant-coefficient difference equations

From playlist Introduction and Background

Searching and Sorting Algorithms (part 4 of 4)

Introductory coverage of basic searching and sorting algorithms, as well as a rudimentary overview of Big-O algorithm analysis. Part of a larger series teaching programming at http://codeschool.org

From playlist Searching and Sorting Algorithms

Post-analysis temporal downsampling

Are your time-frequency results matrices too big? Watch this video to learn how to reduce the temporal resolution of your results to match their temporal precision, which can save lots of time and space. The video uses files you can download from https://github.com/mikexcohen/ANTS_youtube

From playlist OLD ANTS #5) Normalization and time-frequency post-processing

8 2 Randomized Selection Analysis 21 min

From playlist Algorithms 1

Computational Methods for Numerical Relativity, Part 3 Frans Pretorius

Computational Methods for Numerical Relativity, Part 3 Frans Pretorius Princeton University July 22, 2009

From playlist PiTP 2009

Big O Part 7 – Space Complexity versus Time Complexity

This is the seventh in a series of videos about using Big O notation to describe the complexity of an algorithm. That is, how the performance of an algorithm varies according to the amount of input data. This particular video looks at the time complexity, and space complexity, of three w

From playlist Big O Complexity

Transformer (Attention is all you need)

understanding Transformer with its key concepts (attention, multi head attention, positional encoding, residual connection label smoothing) with example. all machine learning youtube videos from me, https://www.youtube.com/playlist?list=PLVNY1HnUlO26x597OgAN8TCgGTiE-38D6

From playlist Machine Learning

Introduction to Machine Learning with Time Series || Markus Loning

Time series are ubiquitous in real-world applications, but often add considerable complications to data science workflows. What’s more, most available machine learning toolboxes (e.g. scikit-learn) are limited to the tabular setting, and cannot easily be applied to time series data. In th

From playlist Machine Learning

Convolution in the time domain

Now that you understand the Fourier transform, it's time to start learning about time-frequency analyses. Convolution is one of the best ways to extract time-frequency dynamics from a time series. Convolution can be conceptualized and implemented in the time domain or in the frequency doma

From playlist OLD ANTS #3) Time-frequency analysis via Morlet wavelet convolution

2020.04.23 Mathias Beiglböck - All adapted topologies are equal

From playlist One World Probability Seminar

Automatically Generating Personalized Adaptive User Interfaces

May 2, 2008 lecture by Krzysztof Gajos for the Stanford University Human Computer Interaction Seminar (CS547). User Interfaces delivered with today's software are usually created in a one-size-fits-all manner, making implicit assumptions about the needs, abilities, and preferences of th

From playlist Course | Human-Computer Interaction Seminar (2007-2008)

Hans Föllmer: Entropy, energy, and optimal couplings on Wiener space

HYBRID EVENT Recorded during the meeting "Advances in Stochastic Control and Optimal Stopping with Applications in Economics and Finance" the September 12, 2022 by the Centre International de Rencontres Mathématiques (Marseille, France) Filmmaker: Guillaume Hennenfent Find this video a

From playlist Probability and Statistics

Sohini Ramachandran: "Genomic Reconstructions of Deep Human History"

Computational Genomics Summer Institute 2016 "Genomic Reconstructions of Deep Human History" Sohini Ramachandran, Brown University Institute for Pure and Applied Mathematics, UCLA July 19, 2016 For more information: http://computationalgenomics.bioinformatics.ucla.edu/

From playlist Computational Genomics Summer Institute 2016

Irene Balelli - Branching random walks applied to antibody affinity maturation

http://www.lesprobabilitesdedemain.fr/index.html Organisateurs : Céline Abraham, Linxiao Chen, Pascal Maillard, Bastien Mallein et la Fondation Sciences Mathématiques de Paris Antibody affinity maturation is a key process in adaptive immunity: it’s a mechanism which allows B-cells to pro

From playlist Les probabilités de demain 2016

Adaptive schemes for MCMC in infinite dimensions by Sreekar Vadlamani

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

Edward Ionides: Island filters for inference on metapopulation dynamics

Low-dimensional compartment models for biological systems can be fitted to time series data using Monte Carlo particle filter methods. As dimension increases, for example when analyzing a collection of spatially coupled populations, particle filter methods rapidly degenerate. We show that

From playlist Probability and Statistics

Josh Bongard - A xither of xenobots: demolishing dichotomous thinking with synthetic proto-organisms

Recorded 17 February 2022. Josh Bongard of the University of Vermont presents "A xither of xenobots: demolishing dichotomous thinking with synthetic proto-organisms" at IPAM's Mathematics of Collective Intelligence Workshop. Learn more online at: http://www.ipam.ucla.edu/programs/workshops

From playlist Workshop: Mathematics of Collective Intelligence - Feb. 15 - 19, 2022.

Somatosensation | Processing the Environment | MCAT | Khan Academy

Explore our ability to sense the environment through our body. By Ron. Created by Ronald Sahyouni. Watch the next lesson: https://www.khanacademy.org/test-prep/mcat/processing-the-environment/somatosensation/v/sensory-adaptation-and-amplification?utm_source=YT&utm_medium=Desc&utm_campaign

From playlist Processing the environment | MCAT | Khan Academy

Multitaper

The final time-frequency analysis method shown here is the multitaper method. It is an extention of the STFFT that can be useful in low-SNR situations. The video uses files you can download from https://github.com/mikexcohen/ANTS_youtube_videos For more online courses about programming,

From playlist OLD ANTS #4) Time-frequency analysis via other methods

2 Ruediger - Stochastic Integration & SDEs

PROGRAM NAME :WINTER SCHOOL ON STOCHASTIC ANALYSIS AND CONTROL OF FLUID FLOW DATES Monday 03 Dec, 2012 - Thursday 20 Dec, 2012 VENUE School of Mathematics, Indian Institute of Science Education and Research, Thiruvananthapuram Stochastic analysis and control of fluid flow problems have

From playlist Winter School on Stochastic Analysis and Control of Fluid Flow