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ORCIDIEEE Signal Processing Magazine, Volume 37
Volume 37, Number 1, January 2020
- Jeffrey A. Fessler
:
Optimization Methods for Magnetic Resonance Image Reconstruction: Key Models and Optimization Algorithms. 33-40 - Justin P. Haldar, Kawin Setsompop:
Linear Predictability in Magnetic Resonance Imaging Reconstruction: Leveraging Shift-Invariant Fourier Structure for Faster and Better Imaging. 69-82 - Bihan Wen, Saiprasad Ravishankar, Luke Pfister, Yoram Bresler:
Transform Learning for Magnetic Resonance Image Reconstruction: From Model-Based Learning to Building Neural Networks. 41-53 - Jonathan I. Tamir, Frank Ong, Suma Anand, Ekin Karasan, Ke Wang, Michael Lustig:
Computational MRI With Physics-Based Constraints: Application to Multicontrast and Quantitative Imaging. 94-104 - Mathews Jacob, Merry P. Mani, Jong Chul Ye:
Structured Low-Rank Algorithms: Theory, Magnetic Resonance Applications, and Links to Machine Learning. 54-68 - Ali H. Sayed:
If You Cannot Come to Us, We Will Go to You... [President's Message]. 5-7 - Rizwan Ahmad, Charles A. Bouman, Gregery T. Buzzard, Stanley H. Chan, Sizhuo Liu, Edward T. Reehorst, Philip Schniter:
Plug-and-Play Methods for Magnetic Resonance Imaging: Using Denoisers for Image Recovery. 105-116 - Anthony G. Christodoulou, Sajan Goud Lingala:
Accelerated Dynamic Magnetic Resonance Imaging Using Learned Representations: A New Frontier in Biomedical Imaging. 83-93 - Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya:
Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. 128-140 - Ljubisa Stankovic, Danilo P. Mandic, Milos Dakovic, Ilya Kisil:
Demystifying the Coherence Index in Compressive Sensing [Lecture Notes]. 152-162 - Mariya Doneva:
Mathematical Models for Magnetic Resonance Imaging Reconstruction: An Overview of the Approaches, Problems, and Future Research Areas. 24-32 - Mónica F. Bugallo, Luis Castedo:
EUSIPCO 2019: A Chronicle of the 27th European Signal Processing Conference in A Coruna, Spain: Looking Into the Future of Signal Processing [Conference Highlights]. 163-168 - Natalie Krauser:
Remembering James Spilker, Jr., Stanford Professor and Pioneer of GPS Technology: The IEEE Life Fellow's Contributions Opened the Door for More Advanced Navigation Systems [In Memoriam]. 14-15 - John Edwards:
Signal Processing Inspires Network Innovation: Signal Processing Is the Key as Researchers Work to Boost Network Speed and Capacity [Special Reports]. 16-23 - Mathews Jacob, Jong Chul Ye, Leslie Ying, Mariya Doneva:
Computational MRI: Compressive Sensing and Beyond [From the Guest Editors]. 21-23 - Christopher M. Sandino, Joseph Y. Cheng, Feiyu Chen, Morteza Mardani, John M. Pauly, Shreyas S. Vasanawala:
Compressed Sensing: From Research to Clinical Practice With Deep Neural Networks: Shortening Scan Times for Magnetic Resonance Imaging. 117-127 - Robert W. Heath Jr.:
Submitting Columns and Forums to SPM [From the Editor]. 3-4 - Dong Liang, Jing Cheng, Ziwen Ke, Leslie Ying:
Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks. 141-151
Volume 37, Number 2, March 2020
- Robert W. Heath Jr.:
What Does an Editor-in-Chief of IEEE Signal Processing Magazine Do, Anyway? [From the Editor]. 3-4 - John Edwards:
Robotics Rolls Into High Gear With Signal Processing: A robotics revolution promises to transform global industries and services, and signal processing is at the forefront [Special Reports]. 10-13 - Soheil Mohajer, Itsik Bergel, Giuseppe Caire:
Cooperative Wireless Mobile Caching: A Signal Processing Perspective. 18-38 - Yuejie Chi, Maxime Ferreira Da Costa:
Harnessing Sparsity Over the Continuum: Atomic norm minimization for superresolution. 39-57 - Tamir Bendory, Alberto Bartesaghi, Amit Singer:
Single-Particle Cryo-Electron Microscopy: Mathematical Theory, Computational Challenges, and Opportunities. 58-76 - Ming Zhang, Xiaoming Chen:
The Importance of Continuity for Linear Time-Invariant Systems [Lecture Notes]. 77-100 - Leonardo Chiariglione:
Delivering Standards to Industries: The MPEG Case [Standards in a Nutshell]. 81-88 - Panos Kudumakis, Thomas Wilmering, Mark B. Sandler, Víctor Rodríguez-Doncel, Laurent Boch, Jaime Delgado:
The Challenge: From MPEG Intellectual Property Rights Ontologies to Smart Contracts and Blockchains [Standards in a Nutshell]. 89-95 - Robert M. Gray:
In Memory of A.H. "Steen" Gray Jr. [Reflections]. 96-100 - José C. M. Bermudez, Mónica F. Bugallo, Alle-Jan van der Veen:
Highlights From the Signal Processing Theory and Methods Technical Committee [In the Spotlight]. 102-104
Volume 37, Number 3, May 2020
- Robert W. Heath Jr.:
Revisiting Research on Signal Processing for Communications in a Pandemic [From the Editor]. 3-5 - Ahmed H. Tewfik:
The Year of Living Dangerously [President's Message]. 6-7 - John Edwards:
Photo and Video Technologies Target New Frontiers: Innovative Imaging Research Enabled by Signal Processing Is Making Cameras More Powerful and Versatile [Special Reports]. 8-167 - Waheed U. Bajwa, Volkan Cevher, Dimitris S. Papailiopoulos, Anna Scaglione:
Machine Learning From Distributed, Streaming Data [From the Guest Editors]. 11-13 - Roula Nassif, Stefan Vlaski, Cédric Richard, Jie Chen, Ali H. Sayed:
Multitask Learning Over Graphs: An Approach for Distributed, Streaming Machine Learning. 14-25 - Tsung-Hui Chang, Mingyi Hong, Hoi-To Wai, Xinwei Zhang, Songtao Lu:
Distributed Learning in the Nonconvex World: From batch data to streaming and beyond. 26-38 - Xiaodong Cui, Wei Zhang, Ulrich Finkler, George Saon, Michael Picheny, David S. Kung:
Distributed Training of Deep Neural Network Acoustic Models for Automatic Speech Recognition: A comparison of current training strategies. 39-49 - Tian Li, Anit Kumar Sahu, Ameet Talwalkar, Virginia Smith:
Federated Learning: Challenges, Methods, and Future Directions. 50-60 - Alec Koppel, Amrit Singh Bedi, Ketan Rajawat, Brian M. Sadler:
Optimally Compressed Nonparametric Online Learning: Tradeoffs between memory and consistency. 61-70 - Emiliano Dall'Anese, Andrea Simonetto, Stephen Becker, Liam Madden:
Optimization and Learning With Information Streams: Time-varying algorithms and applications. 71-83 - Xiao Xu, Qing Zhao:
Distributed No-Regret Learning in Multiagent Systems: Challenges and Recent Developments. 84-91 - Angelia Nedic:
Distributed Gradient Methods for Convex Machine Learning Problems in Networks: Distributed Optimization. 92-101 - Ran Xin, Soummya Kar, Usman A. Khan:
Decentralized Stochastic Optimization and Machine Learning: A Unified Variance-Reduction Framework for Robust Performance and Fast Convergence. 102-113 - Shi Pu, Alex Olshevsky, Ioannis Ch. Paschalidis:
Asymptotic Network Independence in Distributed Stochastic Optimization for Machine Learning: Examining Distributed and Centralized Stochastic Gradient Descent. 114-122 - Donghwan Lee, Niao He, Parameswaran Kamalaruban, Volkan Cevher:
Optimization for Reinforcement Learning: From a single agent to cooperative agents. 123-135 - Aditya Ramamoorthy, Anindya Bijoy Das, Li Tang:
Straggler-Resistant Distributed Matrix Computation via Coding Theory: Removing a Bottleneck in Large-Scale Data Processing. 136-145 - Zhixiong Yang, Arpita Gang, Waheed U. Bajwa:
Adversary-Resilient Distributed and Decentralized Statistical Inference and Machine Learning: An Overview of Recent Advances Under the Byzantine Threat Model. 146-159 - Kiho Choi, Jianle Chen, Dmytro Rusanovskyy, Kwang-Pyo Choi, Euee S. Jang:
An Overview of the MPEG-5 Essential Video Coding Standard [Standards in a Nutshell]. 160-167 - Girmaw Abebe Tadesse, Oliver Bent, Lucio Marcenaro, Komminist Weldemariam, Andrea Cavallaro:
Privacy-Aware Human Activity Recognition From a Wearable Camera: Highlights From the IEEE Video And Image Processing Cup 2019 Student Competition [SP Competitions]. 168-172 - Anderson de Rezende Rocha:
The Information Forensics and Security Technical Committee: Then, Now, and in the Future [In the Spotlight]. 175-176
Volume 37, Number 4, July 2020
- Robert W. Heath Jr.:
Communications and Sensing: An Opportunity for Automotive Systems [From the Editor]. 3-13 - Ahmed H. Tewfik:
Audere est Facere [President's Message]. 5-6 - John Edwards:
Signal Processing Advances Undersea Research: Subsea Research Presents Unique Challenges that Signal Processing Is Helping to Address [Special Reports]. 7-10 - Lina J. Karam, Jay Katupitiya, Vicente Milanés, Ioannis Pitas, Jieping Ye:
Autonomous Driving: Part 1-Sensing and Perception [From the Guest Editors]. 11-13 - Apostolos Modas, Ricardo Sanchez-Matilla, Pascal Frossard, Andrea Cavallaro:
Toward Robust Sensing for Autonomous Vehicles: An Adversarial Perspective. 14-23 - Christoph Stöckle, Stephan Herrmann, Tobias Dirndorfer, Wolfgang Utschick:
Automated Vehicular Safety Systems: Robust Function and Sensor Design. 24-33 - Guang Chen, Hu Cao, Jörg Conradt, Huajin Tang, Florian Röhrbein, Alois C. Knoll:
Event-Based Neuromorphic Vision for Autonomous Driving: A Paradigm Shift for Bio-Inspired Visual Sensing and Perception. 34-49 - You Li, Javier Ibañez-Guzmán:
Lidar for Autonomous Driving: The Principles, Challenges, and Trends for Automotive Lidar and Perception Systems. 50-61 - Joshua Rapp, Julián Tachella, Yoann Altmann, Stephen McLaughlin, Vivek K. Goyal:
Advances in Single-Photon Lidar for Autonomous Vehicles: Working Principles, Challenges, and Recent Advances. 62-71 - Canan Aydogdu, Musa Furkan Keskin, Gisela K. Carvajal, Olof Eriksson, Hans Hellsten, Hans Herbertsson, Emil Nilsson, Mats Rydström, Karl Vanas, Henk Wymeersch:
Radar Interference Mitigation for Automated Driving: Exploring Proactive Strategies. 72-84 - Dingyou Ma, Nir Shlezinger, Tianyao Huang, Yimin Liu, Yonina C. Eldar:
Joint Radar-Communication Strategies for Autonomous Vehicles: Combining Two Key Automotive Technologies. 85-97 - Shunqiao Sun, Athina P. Petropulu, H. Vincent Poor:
MIMO Radar for Advanced Driver-Assistance Systems and Autonomous Driving: Advantages and Challenges. 98-117 - Ulisses M. Braga-Neto, Edward R. Dougherty:
Machine Learning Requires Probability and Statistics [Perspectives]. 118-122 - Soheil Kolouri, Xuwang Yin, Gustavo K. Rohde:
Neural Networks, Hypersurfaces, and the Generalized Radon Transform [Lecture Notes]. 123-133 - László Sujbert, Gyula Simon, Gábor Péceli:
An Observer-Based Adaptive Fourier Analysis [Tips & Tricks]. 134-143 - Maria S. Cross, Andrea Cavallaro:
Privacy as a Feature for Body-Worn Cameras [In the Spotlight]. 145-148
Volume 37, Number 5, September 2020
- Robert W. Heath Jr.:
Reflections on Tutorials and Surveys [From the Editor]. 3-4 - Ahmed H. Tewfik:
That This Nation, Under God, Shall Have a New Birth of Freedom [President's Message]. 5 - Ali H. Sayed:
Election of Regional Directors-at-Large and Members-at-Large [Society News]. 6-7 - H. Vicky Zhao:
Top Downloads in IEEE Xplore [Reader's Choice]. 8-10 - John Edwards:
Three New Imaging Technologies That Are Worth a Look: Aided by Signal Processing, Advanced Imaging Research Projects Are Opening Doors to New Vistas [Special Reports]. 11-14 - Anthony Man-Cho So, Prateek Jain, Wing-Kin Ma, Gesualdo Scutari:
Nonconvex Optimization for Signal Processing and Machine Learning [From the Guest Editors]. 15-17 - Jiajin Li, Anthony Man-Cho So, Wing-Kin Ma:
Understanding Notions of Stationarity in Nonsmooth Optimization: A Guided Tour of Various Constructions of Subdifferential for Nonsmooth Functions. 18-31 - Frank E. Curtis, Katya Scheinberg:
Adaptive Stochastic Optimization: A Framework for Analyzing Stochastic Optimization Algorithms. 32-42 - Sijia Liu, Pin-Yu Chen, Bhavya Kailkhura, Gaoyuan Zhang, Alfred O. Hero III, Pramod K. Varshney:
A Primer on Zeroth-Order Optimization in Signal Processing and Machine Learning: Principals, Recent Advances, and Applications. 43-54 - Meisam Razaviyayn, Tianjian Huang, Songtao Lu, Maher Nouiehed, Maziar Sanjabi, Mingyi Hong:
Nonconvex Min-Max Optimization: Applications, Challenges, and Recent Theoretical Advances. 55-66 - Namrata Vaswani:
Nonconvex Structured Phase Retrieval: A Focus on Provably Correct Approaches. 67-77 - Xiao Fu, Nico Vervliet, Lieven De Lathauwer, Kejun Huang, Nicolas Gillis:
Computing Large-Scale Matrix and Tensor Decomposition With Structured Factors: A Unified Nonconvex Optimization Perspective. 78-94 - Ruoyu Sun, Dawei Li, Shiyu Liang, Tian Ding, Rayadurgam Srikant:
The Global Landscape of Neural Networks: An Overview. 95-108 - Jonathan H. Manton:
Geometry, Manifolds, and Nonconvex Optimization: How Geometry Can Help Optimization. 109-119 - Ehsan Tohidi, Rouhollah Amiri, Mario Coutino, David Gesbert, Geert Leus, Amin Karbasi:
Submodularity in Action: From Machine Learning to Signal Processing Applications. 120-133 - Emil Björnson, Pontus Giselsson:
Two Applications of Deep Learning in the Physical Layer of Communication Systems [Lecture Notes]. 134-140 - Chun-Lin Liu, Soo-Chang Pei:
Closed-Form Output Response of Discrete-Time Linear Time-Invariant Systems Using Intermediate Auxiliary Functions [Lecture Notes]. 140-145 - Ana I. Pérez-Neira, Xavier Mestre:
A Green ICASSP 2020 in Virtual Barcelona [Conference Highlights]. 146-151 - Damian Campo, David Martín, Lucio Marcenaro:
Unsupervised Anomaly Detection Using Intelligent and Heterogeneous Autonomous Systems: Highlights From the 2020 IEEE Signal Processing Cup Student Competition [SP Competitions]. 152-157 - Wei Liu, Mohammad Reza Anbiyaei, Xue Jiang, Lei Zhang, Lucio Marcenaro:
Let There Be a Beam: Highlights From the 2020 IEEE Five-Minute Video Clip Contest [SP Competitions]. 157-162
Volume 37, Number 6, November 2020
- Robert W. Heath Jr.:
Signing Off as Editor-in-Chief [From the Editor]. 3-4 - H. Vicky Zhao:
Top Downloads in IEEE Xplore [Reader's Choice]. 5-191 - John Edwards:
Three Important Audio Projects You'll Want to Hear About: Signal Processing Is Playing an Essential Role in the Development of a New Generation of Audio-Based Applications Targeting Security and Safety [Special Reports]. 7-10 - Antonio G. Marques, Negar Kiyavash, José M. F. Moura, Dimitri Van De Ville, Rebecca Willett:
Graph Signal Processing: Foundations and Emerging Directions [From the Guest Editors]. 11-13 - Yuichi Tanaka, Yonina C. Eldar, Antonio Ortega, Gene Cheung:
Sampling Signals on Graphs: From Theory to Applications. 14-30 - Daniel L. Lau, Gonzalo R. Arce, Alejandro Parada-Mayorga, Daniela Dapena, Karelia Pena-Pena:
Blue-Noise Sampling of Graph and Multigraph Signals: Dithering on Non-Euclidean Domains. 31-42 - David I. Shuman:
Localized Spectral Graph Filter Frames: A Unifying Framework, Survey of Design Considerations, and Numerical Comparison. 43-63 - Oguzhan Teke, P. P. Vaidyanathan:
Random Node-Asynchronous Graph Computations: Novel Opportunities for Discrete-Time State-Space Recursions. 64-73 - Raksha Ramakrishna, Hoi-To Wai, Anna Scaglione:
A User Guide to Low-Pass Graph Signal Processing and Its Applications: Tools and Applications. 74-85 - Thomas Dittrich, Gerald Matz:
Signal Processing on Signed Graphs: Fundamentals and Potentials. 86-98 - Antonio G. Marques, Santiago Segarra, Gonzalo Mateos:
Signal Processing on Directed Graphs: The Role of Edge Directionality When Processing and Learning From Network Data. 99-116 - Xiaowen Dong, Dorina Thanou, Laura Toni, Michael M. Bronstein, Pascal Frossard:
Graph Signal Processing for Machine Learning: A Review and New Perspectives. 117-127 - Fernando Gama, Elvin Isufi, Geert Leus, Alejandro Ribeiro:
Graphs, Convolutions, and Neural Networks: From Graph Filters to Graph Neural Networks. 128-138 - Mark Cheung, John Shi, Oren Wright, Lavender Yao Jiang, Xujin Liu, José M. F. Moura:
Graph Signal Processing and Deep Learning: Convolution, Pooling, and Topology. 139-149 - Miljan Petrovic, Raphaël Liégeois, Thomas William Arthur Bolton, Dimitri Van De Ville:
Community-Aware Graph Signal Processing: Modularity Defines New Ways of Processing Graph Signals. 150-159 - Jay S. Stanley III, Eric C. Chi, Gal Mishne:
Multiway Graph Signal Processing on Tensors: Integrative Analysis of Irregular Geometries. 160-173 - Sergio Barbarossa, Stefania Sardellitti:
Topological Signal Processing: Making Sense of Data Building on Multiway Relations. 174-183 - Utku Demir, Gaurav Sharma:
SigPrep: Open Source Web-Based Prework for Signals and Systems [SP Education]. 184-191 - Xiang-Gen Xia:
Undesired Cross Terms [Lecture Notes]. 192-195 - Mohamed Rasheed-Hilmy Abdalmoaty, Håkan Hjalmarsson, Bo Wahlberg:
The Gaussian Maximum-Likelihood Estimator Versus the Optimally Weighted Least-Squares Estimator [Lecture Notes]. 195-199 - Bhaskar D. Rao, Zheng-Hua Tan:
Highlights From the Machine Learning for Signal Processing Technical Committee [In the Spotlight]. 200-202
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