Multidimensional signal processing
Two dimensional filters have seen substantial development effort due to their importance and high applicability across several domains. In the 2-D case the situation is quite different from the 1-D case, because the multi-dimensional polynomials cannot in general be factored. This means that an arbitrary transfer function cannot generally be manipulated into a form required by a particular implementation. The input-output relationship of a 2-D IIR filter obeys a constant-coefficient linear partial difference equation from which the value of an output sample can be computed using the input samples and previously computed output samples. Because the values of the output samples are fed back, the 2-D filter, like its 1-D counterpart, can be unstable. (Wikipedia).
The Two-Dimensional Discrete Fourier Transform
The two-dimensional discrete Fourier transform (DFT) is the natural extension of the one-dimensional DFT and describes two-dimensional signals like images as a weighted sum of two dimensional sinusoids. Two-dimensional sinusoids have a horizontal frequency component and a vertical frequen
From playlist Fourier
reaLD 3D glasses filter with a linear polarising filter
This is for a post on my blog: http://blog.stevemould.com
From playlist Everything in chronological order
From playlist filter (less comfortable)
Introduction to Frequency Selective Filtering
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. Separation of signals based on frequency content using lowpass, highpass, bandpass, etc filters. Filter g
From playlist Introduction to Filter Design
From playlist filter (less comfortable)
Low Pass Filters & High Pass Filters : Data Science Concepts
What is a low pass filter? What is a high pass filter? Sobel Filter: https://en.wikipedia.org/wiki/Sobel_operator
From playlist Time Series Analysis
Physics 60 Optics: Double Slit Interference (2 of 25) Phase Difference and Double Slit
Visit http://ilectureonline.com for more math and science lectures! In this video I will explain how phase difference is created by light traveling through a double slit.
From playlist PHYSICS 60 INTERFERENCE OF LIGHT
Ramon van Handel - Filtering in high dimension III
PROGRAM: Nonlinear filtering and data assimilation DATES: Wednesday 08 Jan, 2014 - Saturday 11 Jan, 2014 VENUE: ICTS-TIFR, IISc Campus, Bangalore LINK:http://www.icts.res.in/discussion_meeting/NFDA2014/ The applications of the framework of filtering theory to the problem of data assimi
From playlist Nonlinear filtering and data assimilation
Gang George Yin: "High-Dimensional HJBs: Mean-Field Limits and McKean-Vlasov Equations"
High Dimensional Hamilton-Jacobi PDEs 2020 Workshop I: High Dimensional Hamilton-Jacobi Methods in Control and Differential Games "High-Dimensional HJBs: Mean-Field Limits and McKean-Vlasov Equations" Gang George Yin, Wayne State University Abstract: In this talk, we will study mean-fiel
From playlist High Dimensional Hamilton-Jacobi PDEs 2020
Physics 60 Optics: Double Slit Interference (15 of 25) Find Phase Difference and Intensity
Visit http://ilectureonline.com for more math and science lectures! . In this video I will find the phase difference and intensity of 2 broadcasting tower 20m apart.
From playlist PHYSICS 60 INTERFERENCE OF LIGHT
Sri Namachchivaya - Stability, dimensional reduction and data assimilation in random dynamical sy
PROGRAM: Nonlinear filtering and data assimilation DATES: Wednesday 08 Jan, 2014 - Saturday 11 Jan, 2014 VENUE: ICTS-TIFR, IISc Campus, Bangalore LINK:http://www.icts.res.in/discussion_meeting/NFDA2014/ The applications of the framework of filtering theory to the problem of data assimi
From playlist Nonlinear filtering and data assimilation
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
PROGRAM: Nonlinear filtering and data assimilation DATES: Wednesday 08 Jan, 2014 - Saturday 11 Jan, 2014 VENUE: ICTS-TIFR, IISc Campus, Bangalore LINK:http://www.icts.res.in/discussion_meeting/NFDA2014/ The applications of the framework of filtering theory to the problem of data assimi
From playlist Nonlinear filtering and data assimilation
Duality between estimation and control - Sanjoy Mitter
PROGRAM: Data Assimilation Research Program Venue: Centre for Applicable Mathematics-TIFR and Indian Institute of Science Dates: 04 - 23 July, 2011 DESCRIPTION: Data assimilation (DA) is a powerful and versatile method for combining observational data of a system with its dynamical mod
From playlist Data Assimilation Research Program
Sri Namachchivaya - Stability, dimensional reduction and data assimilation in random dynamical s
PROGRAM: Nonlinear filtering and data assimilation DATES: Wednesday 08 Jan, 2014 - Saturday 11 Jan, 2014 VENUE: ICTS-TIFR, IISc Campus, Bangalore LINK:http://www.icts.res.in/discussion_meeting/NFDA2014/ The applications of the framework of filtering theory to the problem of data assimi
From playlist Nonlinear filtering and data assimilation
Sri Namachchivaya - Stability, dimensional reduction and data assimilation in random dynamical sy
PROGRAM: Nonlinear filtering and data assimilation DATES: Wednesday 08 Jan, 2014 - Saturday 11 Jan, 2014 VENUE: ICTS-TIFR, IISc Campus, Bangalore LINK:http://www.icts.res.in/discussion_meeting/NFDA2014/ The applications of the framework of filtering theory to the problem of data assimi
From playlist Nonlinear filtering and data assimilation
AMMI 2022 Course "Geometric Deep Learning" - Lecture 8 (Groups & Homogeneous spaces) - Taco Cohen
Video recording of the course "Geometric Deep Learning" taught in the African Master in Machine Intelligence in July 2022 by Michael Bronstein (Oxford), Joan Bruna (NYU), Taco Cohen (Qualcomm), and Petar Veličković (DeepMind) Lecture 8: Group convolution • Regular representation • Spheric
From playlist AMMI Geometric Deep Learning Course - Second Edition (2022)
TensorFlow Tutorial #02 Convolutional Neural Network
How to make a Convolutional Neural Network in TensorFlow for recognizing handwritten digits from the MNIST data-set. This tutorial has been updated to work with TensorFlow 2.1 and possibly later versions using "v.1 compatibility mode". https://github.com/Hvass-Labs/TensorFlow-Tutorials
From playlist Deep Learning
http://AllSignalProcessing.com for more great signal processing content, including concept/screenshot files, quizzes, MATLAB and data files. Noncausal filtering of stored data to obtain zero-phase response using the time-reversal property of the DFT, as implemented by the "filtfilt" comma
From playlist Introduction to Filter Design