Generalized Blue Noise Sampling On Graphs And Applications
DOWNLOAD
Download Generalized Blue Noise Sampling On Graphs And Applications PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Generalized Blue Noise Sampling On Graphs And Applications book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Generalized Blue Noise Sampling On Graphs And Applications
DOWNLOAD
Author : Maria Daniela Dapena Rivero
language : en
Publisher:
Release Date : 2022
Generalized Blue Noise Sampling On Graphs And Applications written by Maria Daniela Dapena Rivero and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Graph Signal Processing (GSP) extends classical signal processing to the analysis of signals supported over irregular grids represented by graphs. Sampling and reconstruction are fundamental tools that have received considerable attention in GSP. Under the assumption that adjacent nodes tend to have similar signal values, a reconstruction method that recovers a signal by minimizing its variation with respect to the graph structure is proposed. To this end, the mean square error of the recovered signal is minimized by sampling sets whose spectrum presents high-frequency dominance, a characteristic present in blue-noise patterns that suppress the low-frequency components by maximizing the inter-sample distance. Blue-noise sampling has many advantages, including the possibility of finding close to optimal sampling performance using simple distance concepts. However, the formulation of blue-noise sampling is restricted to graphs with regular structures, and most applications involve irregular graphs. Thus, the underlying principles of blue-noise sampling need to be considered in a broader sense. Another limitation of blue noise is its high computational complexity, limiting its use to small graphs. This work overcomes these limitations and generalizes blue-noise sampling to large and irregular graphs. First, blue-noise sampling is generalized to irregular graphs by regularizing the weights across the edges of the graph before sampling, such that the concentration of samples is adapted to the local density of nodes. Secondly, a new and scalable approach can be easily parallelized to leverage the massive parallel processing power readily available in commodity hardware is proposed. The proposed method uses graph partitioning algorithms in concert with vertex-domain blue-noise sampling to develop two sampling schemes that minimize the recovery error and are based on the spatial characteristic of the graph. The first sampling scheme combines graph partitioning with the void-and-cluster algorithm. The second approach uses error diffusion in the partitions. Experiments on synthetic and real data show the effectiveness of these new approaches on very large graphs. Then, the partitions are used to recover the signal by adding some overlapping, which induces smoothness in the recovered signal within and between partitions. Finally, the benefits of blue-noise sampling on graphs are extended outside of GSP to the active form of semi-supervised learning to reduce the amount of labeled data needed by the machine learning algorithms to achieve high accuracy.
Blue Noise And Optimal Sampling On Graphs
DOWNLOAD
Author : Alejandro Parada-Mayorga
language : en
Publisher:
Release Date : 2019
Blue Noise And Optimal Sampling On Graphs written by Alejandro Parada-Mayorga and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
In the second part of this dissertation we consider the problem of sampling on regular grids for compressed sensing applications. We design optimal sampling patterns in coded apertures for CASSI systems and compressive X-ray tomosynthesis architectures, providing closed form solutions that outperform the results achieved using designs obtained with previous approaches, at a very low computational cost. Additionally, a rigorous estimate of the spectral resolution in general colored CASSI systems is provided exploiting the structure of the non-ideal sampling patterns obtained when wide spectral filters are considered.
Graph Representation Learning
DOWNLOAD
Author : William L. William L. Hamilton
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Graph Representation Learning written by William L. William L. Hamilton and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
Generalized Concavity
DOWNLOAD
Author : Mordecai Avriel
language : en
Publisher: SIAM
Release Date : 2010-11-25
Generalized Concavity written by Mordecai Avriel and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-25 with Mathematics categories.
Originally published: New York: Plenum Press, 1988.
Introduction To Graph Signal Processing
DOWNLOAD
Author : Antonio Ortega
language : en
Publisher: Cambridge University Press
Release Date : 2022-06-09
Introduction To Graph Signal Processing written by Antonio Ortega and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-09 with Technology & Engineering categories.
An intuitive and accessible text explaining the fundamentals and applications of graph signal processing. Requiring only an elementary understanding of linear algebra, it covers both basic and advanced topics, including node domain processing, graph signal frequency, sampling, and graph signal representations, as well as how to choose a graph. Understand the basic insights behind key concepts and learn how graphs can be associated to a range of specific applications across physical, biological and social networks, distributed sensor networks, image and video processing, and machine learning. With numerous exercises and Matlab examples to help put knowledge into practice, and a solutions manual available online for instructors, this unique text is essential reading for graduate and senior undergraduate students taking courses on graph signal processing, signal processing, information processing, and data analysis, as well as researchers and industry professionals.
Digital Halftoning
DOWNLOAD
Author : Robert Ulichney
language : en
Publisher: MIT Press
Release Date : 1987
Digital Halftoning written by Robert Ulichney and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Computers categories.
Physical reconstruction function. Tools for fourier analysis. Dithering with white noise. Clustered-dot ordered dither. Dispersed-dot ordered dither. Ordered dither on asymmetric grids. Dithering with blue noise. Concluding remarks. Glossary of principal symbols. References. Index.
Factor Graphs For Robot Perception
DOWNLOAD
Author : Frank Dellaert
language : en
Publisher:
Release Date : 2017-08-15
Factor Graphs For Robot Perception written by Frank Dellaert and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-08-15 with Technology & Engineering categories.
Reviews the use of factor graphs for the modeling and solving of large-scale inference problems in robotics. Factor graphs are introduced as an economical representation within which to formulate the different inference problems, setting the stage for the subsequent sections on practical methods to solve them.
Sampling Theory
DOWNLOAD
Author : Yonina C. Eldar
language : en
Publisher: Cambridge University Press
Release Date : 2015-04-09
Sampling Theory written by Yonina C. Eldar and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-09 with Computers categories.
A comprehensive guide to sampling for engineers, covering the fundamental mathematical underpinnings together with practical engineering principles and applications.
High Dimensional Probability
DOWNLOAD
Author : Roman Vershynin
language : en
Publisher: Cambridge University Press
Release Date : 2018-09-27
High Dimensional Probability written by Roman Vershynin and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-27 with Business & Economics categories.
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.
The Fourier Transform And Its Applications
DOWNLOAD
Author : Ronald Newbold Bracewell
language : en
Publisher:
Release Date : 1978
The Fourier Transform And Its Applications written by Ronald Newbold Bracewell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1978 with Fourier transformations categories.