Frequency-domain analysis | Multidimensional signal processing | Signal processing | Signal estimation | Inverse problems | Fourier analysis | Trigonometry

SAMV (algorithm)

SAMV (iterative sparse asymptotic minimum variance) is a parameter-free superresolution algorithm for the linear inverse problem in spectral estimation, direction-of-arrival (DOA) estimation and tomographic reconstruction with applications in signal processing, medical imaging and remote sensing. The name was coined in 2013 to emphasize its basis on the asymptotically minimum variance (AMV) criterion. It is a powerful tool for the recovery of both the amplitude and frequency characteristics of multiple highly correlated sources in challenging environments (e.g., limited number of snapshots and low signal-to-noise ratio). Applications include synthetic-aperture radar, computed tomography scan, and magnetic resonance imaging (MRI). (Wikipedia).

SAMV (algorithm)
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Jana Cslovjecsek: Efficient algorithms for multistage stochastic integer programming using proximity

We consider the problem of solving integer programs of the form min {c^T x : Ax = b; x geq 0}, where A is a multistage stochastic matrix. We give an algorithm that solves this problem in fixed-parameter time f(d; ||A||_infty) n log^O(2d) n, where f is a computable function, d is the treed

From playlist Workshop: Parametrized complexity and discrete optimization

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Using the DFS Algorithm for Finding Long Paths in Random and... Graphs - Michael Krivelevich

Michael Krivelevich Using the DFS Algorithm for Finding Long Paths in Random and Pseudo-Random Graphs Tel Aviv University September 23, 2013 For more videos, visit http://video.ias.edu

From playlist Mathematics

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Introduction to Algorithms - What are they and how are they useful?

#3B1B #SoMe2 This is my submission for this year's SoME, SoME2!! I hope you enjoy, and please feel free to leave any comments. Any feedback is hugely appreciated~! ーーーーーーーーーーーーーーーーーーーーーーー Time Stamps: 00:00 Intro 00:37 Introduction to Algorithms 03:47 Exploring Algorithms - Binary Searc

From playlist Summer of Math Exposition 2 videos

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Function Comparision - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

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Linear Algebra 11q: Algorithm for Calculating the Inverse Matrix

https://bit.ly/PavelPatreon https://lem.ma/LA - Linear Algebra on Lemma http://bit.ly/ITCYTNew - Dr. Grinfeld's Tensor Calculus textbook https://lem.ma/prep - Complete SAT Math Prep

From playlist Part 1 Linear Algebra: An In-Depth Introduction with a Focus on Applications

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2 Construction of a Matrix-YouTube sharing.mov

This video shows you how a matrix is constructed from a set of linear equations. It helps you understand where the various elements in a matrix comes from.

From playlist Linear Algebra

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What is linear algebra?

This is part of an online course on beginner/intermediate linear algebra, which presents theory and implementation in MATLAB and Python. The course is designed for people interested in applying linear algebra to applications in multivariate signal processing, statistics, and data science.

From playlist Linear algebra: theory and implementation

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Measuring Time Solution - Intro to Algorithms

This video is part of an online course, Intro to Algorithms. Check out the course here: https://www.udacity.com/course/cs215.

From playlist Introduction to Algorithms

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【PRIM's Algorithm】 Easy & with Example #SoME1

🚀 A short tutorial on how Prim's Algorithm works. Watching this will make you a real Prim-adonna. 😜 📚 Prim's algorithm is a greedy algorithm that finds a minimum spanning tree (=MST) for a weighted undirected graph. This means it finds a subset of the edges that forms a tree that inclu

From playlist Summer of Math Exposition Youtube Videos

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What Is An Algorithm? | What Exactly Is Algorithm? | Algorithm Basics Explained | Simplilearn

This video explains what is an algorithm in the data structure. This Simplilearn's What Is An Algorithm? tutorial will help beginners to understand what exactly is an algorithm with an example. All of the algorithm basics are explained in this video. Following topics covered in this vi

From playlist Data Structures & Algorithms [2022 Updated]

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Sorting Algorithms Full Course | Sorting Algorithms In Data Structures Explained | Simplilearn

This Simplilearn video is based on The Sorting Algorithms Full Course. This tutorial mainly focuses on all the major Sorting Algorithms In Data Structures Explained with detailed theory and practical examples for providing a better learning experience. This video covers the following Sort

From playlist Simplilearn Live

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Lecture 1 - Introduction to Algorithms

This is Lecture 1 of the CSE373 (Analysis of Algorithms) course taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 2007. The lecture slides are available at: http://www.cs.sunysb.edu/~algorith/video-lectures/2007/lecture1.pdf More informati

From playlist CSE373 - Analysis of Algorithms - 2007 SBU

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Lecture 1 - Introduction to Algorithms

This is Lecture 1 of the CSE373 (Analysis of Algorithms) taught by Professor Steven Skiena [http://www.cs.sunysb.edu/~skiena/] at Stony Brook University in 1997. The lecture slides are available at: http://www.cs.sunysb.edu/~algorith/video-lectures/1997/lecture1.pdf

From playlist CSE373 - Analysis of Algorithms - 1997 SBU

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What Is An Algorithm ? | Introduction to Algorithms | How To Write An Algorithm? | Simplilearn

This video is based on What Is An Algorithm ? The Introduction to Algorithms tutorial will explain to you How To Write An Algorithm? and it will cover the following topics ✅00:00- Introduction to Algorithms ✅01:46- What Is an Algorithm? The algorithm is a step-by-step procedure or set o

From playlist C++ Tutorial Videos

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Stanford Seminar - Participating and Designing around Algorithmic Sociotechnical Systems

Motahhare Eslami Carnegie Mellon University October 4, 2019 Algorithms play a vital role in curating online information in socio-technical systems, however, they are usually housed in black-boxes that limit users' understanding of how an algorithmic decision is made. While this opacity pa

From playlist Stanford Seminars

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Ellen Vitercik: "How much data is sufficient to learn high-performing algorithms?"

Deep Learning and Combinatorial Optimization 2021 "How much data is sufficient to learn high-performing algorithms?" Ellen Vitercik - Carnegie Mellon University Abstract: Algorithms often have tunable parameters that have a considerable impact on their runtime and solution quality. A gro

From playlist Deep Learning and Combinatorial Optimization 2021

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Better Algorithm Intuition

Data structure intuition is something that develops naturally for most software developers. In all languages, we rely heavily on standard containers and collections. Need fast insertion/lookup? Hashmap. Need a sorted data structure that stores unique values? Set. Duplicate values? Multiset

From playlist C++

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Dynamic Graph Algorithms and Their Implementation

Abstract: While many algorithmic graph problems have been solved for static graphs, graphs that are used as models in various applications often change dynamically and, thus, require algorithms that can adapt quickly to the deletion and insertion of edges. I will start with providing an ov

From playlist SIAG-ACDA Online Seminar Series

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Geometric Algorithms: Graham & Jarvis - Lecture 10

All rights reserved for http://www.aduni.org/ Published under the Creative Commons Attribution-ShareAlike license http://creativecommons.org/licenses/by-sa/2.0/ Tutorials by Instructor: Shai Simonson. http://www.stonehill.edu/compsci/shai.htm Visit the forum at: http://www.coderisland.c

From playlist ArsDigita Algorithms by Shai Simonson

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CT scan | Signal processing | Vectorization (mathematics) | Periodogram | MATLAB | Inverse problem | Spectral density estimation | Correlation coefficient | Radon transform | Covariance matrix | Compressed sensing | Pulse-Doppler radar | Matched filter | Pulse compression | Super-resolution imaging | Maximum likelihood estimation | Dirac delta function | Fast Fourier transform | Direction of arrival | Single-input single-output system | Spectral leakage | Signal-to-noise ratio | Array processing | Tomographic reconstruction