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Today’s Rapidly Evolving Education Landscape: Challenges and Opportunities [From the Editor] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Tülay Adali
For reasons beyond our control, the issues of IEEE Signal Processing Magazine arrive to you with delays this year. As you receive the current March issue, we are back from another edition of our flagship conference, the IEEE International Conference on Acoustic, Speech, and Signal Processing (ICASSP), which took place in Seoul, Korea, 14–19 April 2024. It was successful and vibrant, and, with 4,432
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A Signal Processor Teaches Generative Artificial Intelligence [SP Education] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Richard J. Radke
How did an “old dog” signal processing professor approach learning and teaching the “new tricks” of generative artificial intelligence (AI)? This article overviews my recent experience in preparing and delivering a new course called “Computational Creativity,” reflecting on the methods I adopted compared to a traditional equations-on-a-whiteboard course. The technical material is qualitatively different
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Hypercomplex Signal and Image Processing: Part 1 [From the Guest Editors] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Nektarios A. Valous, Eckhard Hitzer, Salvatore Vitabile, Swanhild Bernstein, Carlile Lavor, Derek Abbott, Maria Elena Luna-Elizarrarás, Wilder Lopes
Novel computational signal and image analysis methodologies based on feature-rich mathematical/computational frameworks continue to push the limits of the technological envelope, thus providing optimized and efficient solutions. Hypercomplex signal and image processing is a fascinating field that extends conventional methods by using hypercomplex numbers in a unified framework for algebra and geometry
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Hypercomplex Techniques in Signal and Image Processing Using Network Graph Theory: Identifying core research directions [Hypercomplex Signal and Image Processing] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Alfredo Alcayde, Jorge Ventura, Francisco G. Montoya
This article aims to identify core research directions and provide a comprehensive overview of major advancements in the field of hypercomplex signal and image processing techniques using network graph theory. The methodology employs community detection algorithms on research networks to uncover relationships among researchers and topic fields in the hypercomplex domain. This is accomplished through
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Hypercomplex Processing of Vector Field Seismic Data: Toward vector-valued signal processing [Hypercomplex Signal and Image Processing] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Breno Bahia, Arash JafarGandomi, Mauricio D. Sacchi
Vector-valued signals are crucial in science and engineering. The evolving field of hypercomplex signal processing, particularly quaternion algebra, offers a concise and natural approach to handling vectorial data. In multicomponent seismology, for instance, vector-valued signal processing finds a natural fit that has been exploited in several applications. This article provides a concise and practical
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Split-Quaternions for Perceptual White Balance: A quantum information-based chromatic adaptation transform [Hypercomplex Signal and Image Processing] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Michel Berthier, Nicoletta Prencipe, Edoardo Provenzi
We propose a perceptual chromatic adaptation transform (CAT) for white balance that makes use of split-quaternions. The novelty of the present work, which is motivated by a recently developed quantumlike model of color perception, consists of stressing the link between the algebraic structures appearing in this model and a certain subalgebra of the split-quaternions. We show the potential of this approach
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Holistic Processing of Color Images Using Novel Quaternion-Valued Wavelets on the Plane: A promising transformative tool [Hypercomplex Signal and Image Processing] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Neil D. Dizon, Jeffrey A. Hogan
Recently, novel quaternion-valued wavelets on the plane were constructed using an optimization approach. These wavelets are compactly supported, smooth, orthonormal, nonseparable, and truly quaternionic. However, they have not been tested in application. In this article, we introduce a methodology for decomposing and reconstructing color images using quaternionic wavelet filters associated to recently
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Quaternion-Based Arithmetic in Quantum Information Processing: A promising approach for efficient color quantum imaging [Hypercomplex Signal and Image Processing] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Artyom M. Grigoryan, Sos S. Agaian
Classical color image processing, image recognition, and machine learning introduce nonlinearity, causing the collapse of the quantum state into classical probability perceptrons after measurements, due to the inherent linearity of quantum computing. To address this challenge, quaternion-based arithmetic offers a promising approach. By treating the primary color components as a single unit using quaternion
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Geometric Algebra Quantum Convolutional Neural Network: A model using geometric (Clifford) algebras and quantum computing [Hypercomplex Signal and Image Processing] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Guillermo Altamirano-Escobedo, Eduardo Bayro-Corrochano
A hybrid model called the geometric (Clifford) quanvolutional neural network ( GQNN ) that merges elements of geometric (Clifford) convolutional neural networks (GCNNs) and variational quantum circuits (VQCs) is presented. In this model, a randomized quantum convolution operation is applied to the input image, giving as a result four output channels, which are treated as a single entity (quaternion
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Widely Linear Adaptive Filtering Based on Clifford Geometric Algebra: A unified framework [Hypercomplex Signal and Image Processing] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14 Wenyuan Wang, Kutluyil Doğançay
In this article, we present a powerful unifying framework for widely linear (WL) adaptive filters building on the concept of geometric algebra (GA), including recently proposed complex-valued (CV), quaternion-valued, and GA WL adaptive filters (WLAFs). We also consider and review WL adaptive filtering methods that feature robustness against impulsive noise, noisy input measurements, partial coefficient
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In Memoriam: H. Joel Trussell [In Memoriam] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-06-14
Recounts the career and contributions of H. Joel Trussell.
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TECH RXIV: Share Your Preprint Research with the World! IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16
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2023 IEEE Signal Processing Society Awards [Society News] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16
Presents the recipients of IEEE Signal Processing Society awards for 2023.
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Statistical Principles of Time Reversal [Perspectives] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 K. J. Ray Liu, Beibei Wang
Time reversal is a physical principle well known for its deterministic focusing effect. Recently discovered statistical effects show that the time reversal focusing spot is not a point but has a Bessel power distribution. This finding offers accurate and reliable speed estimation indoors, where multipaths are abundant, with mostly nonline-of-sight (NLOS) conditions, and enable various indoor applications
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Introducing the New Area Editors for SPM [Society News] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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In Memoriam: Allen Gorin [In Memoriam] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16
Recounts the career and contributions of Allen Gorin.
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Kerala Chapter Receives the 2023 Chapter of the Year Award! [Society News] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 Yihua Zhang, Prashant Khanduri, Ioannis Tsaknakis, Yuguang Yao, Mingyi Hong, Sijia Liu
Recently, bilevel optimization (BLO) has taken center stage in some very exciting developments in the area of signal processing (SP) and machine learning (ML). Roughly speaking, BLO is a classical optimization problem that involves two levels of hierarchy (i.e., upper and lower levels), wherein obtaining the solution to the upper-level problem requires solving the lower-level one. BLO has become popular
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SPS Announces the 2024 Class of Distinguished Lecturers and Distinguished Industry Speakers [Society News] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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Going for Sustainable Conferences [Perspectives] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 Ana I. Pérez-Neira
The research landscape is evolving very dynamically. This column reflects on it from a conference viewpoint and focuses on the importance of creating a more sustainable culture for the conference portfolio that the IEEE Signal Processing Society (SPS) offers. Among the different considerations, the role that virtual conferences can play is highlighted.
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IEEE SPS 2023 President-Elect, Members-at-Large, and Regional Directors-at-Large Election Results [Society News] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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An Exciting Juncture for Signal Processing Research: On Building Bridges, Challenges, and Opportunities [From the Editor] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 Tülay Adali
A warm greeting to the signal processing community as I start my term as the editor-in-chief of IEEE Signal Processing Magazine ( SPM ). I hope to be worthy of the confidence invested in me and to be able to follow successfully in Christian Jutten’s footsteps. He led our magazine for three years with dedication and brought timely topics like green signal processing, ethics, and reproducibility to the
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The EXPERIENCE Project: Automatic virtualization of “extended personal reality” through biomedical signal processing and explainable artificial intelligence [Applications Corner] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 Gaetano Valenza, Mariano Alcañiz, Vladimir Carli, Gabriela Dudnik, Claudio Gentili, Jaime Guixeres Provinciale, Simone Rossi, Nicola Toschi, Virginie van Wassenhove
The transformation of communication media has revolutionized social interactions, incorporating audio and video into our lives. Despite the recent availability of virtual reality (VR) technology, its widespread adoption faces obstacles. Technological challenges in creating VR environments and scientific confounding concerning interindividual variability in responses to virtual simulations are key factors
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Bayes’ Rule Using Imprecise Probabilities [Lecture Notes] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 Branko Ristic, Alessio Benavoli, Sanjeev Arulampalam
Bayes’ rule, as one of the fundamental concepts of statistical signal processing, provides a way to update our belief about an event based on the arrival of new pieces of evidence. Uncertainty is traditionally modeled by a probability distribution. Prior belief is thus expressed by a prior probability distribution, while the update involves the likelihood function, a probabilistic expression of how
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A Tutorial on Single-Shot 3D Surface Imaging Techniques [Lecture Notes] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 ZhenZhou Wang
In recent years, noncontact 3D surface imaging techniques have made great progress due to advances in optical devices and image processing. The single-shot technique is essential for 3D surface imaging techniques to accurately calculate the 3D shape information of the irreversible transient surfaces in the high-speed dynamic scene. In this tutorial, we provide a review of recent advances in existing
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Long Polynomial Modular Multiplication Using Low-Complexity Number Theoretic Transform [Lecture Notes] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 Sin-Wei Chiu, Keshab K. Parhi
This tutorial aims to establish connections between polynomial modular multiplication over a ring to circular convolution and the discrete Fourier transform (DFT). The main goal is to extend the well-known theory of the DFT in signal processing (SP) to other applications involving polynomials in a ring, such as homomorphic encryption (HE).
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Signal Processing at 75: More Dynamic and Pervasive Than Ever [Perspectives] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 José M. F. Moura
The year 2023 marked the 75th anniversary of the IEEE Signal Processing Society (SPS), which was founded in 1948 as the “Professional Group on Audio” of the Institute of Radio Engineers (IRE), becoming the first IEEE Society. (The IRE, founded in 1912 with a focus on radio and then electronics, together with the American Institute of Electrical Engineers, founded in 1884 with an emphasis on power and
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Learning From the Hidden Letters [President’s Message] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2024-04-16 Min Wu
The opportunity to write this column as the president of the IEEE Signal Processing Society (SPS) was far beyond my imagination when I first joined the SPS as a graduate student member in the 1990s. Career growth through the eyes of an SPS student member was a long journey filled with uncertainty. And at that time, SPS had few female or Asian leaders to model. Like many of you, I started by joining
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Super-Resolving a Frequency Band [Tips & Tricks] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Ruiming Guo, Thierry Blu
This article introduces a simple formula that provides the exact frequency of a pure sinusoid from just two samples of its discrete-time Fourier transform (DTFT). Even when the signal is not a pure sinusoid, this formula still works in a very good approximation (optimally after a single refinement), paving the way for the high-resolution frequency tracking of quickly varying signals or simply improving
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SPS Members, You Are All Heirs of Fourier! [From the Editor] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Christian Jutten
My three years of service as the editor-in-chief (EIC) of Signal Processing Magazine ( SPM ) are now coming to a close. During the past three years, many of us were deeply affected by serious political, social, and environmental events such as the war in Ukraine; protests for freedom in Iran; coups d’état in Africa; the COVID-19 pandemic; seisms in Turkey, Syria, and Morocco; huge floods in Libya and
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Reflections on the Poland Chapter Celebration [President’s Message] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Athina Petropulu
My end of term as IEEE Signal Processing Society (SPS) president is fast approaching. It has been an incredible experience that has provided me with so many opportunities to engage with our members around the globe, forge relationships with other IEEE Societies, and meet a diverse range of people that I hope will become active members of our Society in the future. It has been a great privilege to be
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Fourier and the Early Days of Sound Analysis [DSP History] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Patrick Flandrin
Joseph Fourier’s methods (and their variants) are omnipresent in audio signal processing. However, it turns out that the underlying ideas took some time to penetrate the field of sound analysis and that different paths were first followed in the period immediately following Fourier’s pioneering work, with or without reference to him. This illustrates the interplay between mathematics and physics as
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Polynomial Eigenvalue Decomposition for Multichannel Broadband Signal Processing: A mathematical technique offering new insights and solutions IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Vincent W. Neo, Soydan Redif, John G. McWhirter, Jennifer Pestana, Ian K. Proudler, Stephan Weiss, Patrick A. Naylor
This article is devoted to the polynomial eigenvalue decomposition (PEVD) and its applications in broadband multichannel signal processing, motivated by the optimum solutions provided by the EVD for the narrowband case [1] , [2] . In general, we would like to extend the utility of the EVD to also address broadband problems. Multichannel broadband signals arise at the core of many essential commercial
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A Signal Processing Interpretation of Noise-Reduction Convolutional Neural Networks: Exploring the mathematical formulation of encoding-decoding CNNs IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Luis Albert Zavala-Mondragón, Peter H.N. de With, Fons van der Sommen
Encoding-decoding convolutional neural networks (CNNs) play a central role in data-driven noise reduction and can be found within numerous deep learning algorithms. However, the development of these CNN architectures is often done in an ad hoc fashion and theoretical underpinnings for important design choices are generally lacking. Up to now, there have been different existing relevant works that have
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Tricks for Designing a Cascade of Infinite Impulse Response Filters With an Almost Linear Phase Response [Tips & Tricks] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 David Shiung, Jeng-Ji Huang, Ya-Yin Yang
Designing filters with perfect frequency responses (i.e., flat passbands, sharp transition bands, highly suppressed stopbands, and linear phase responses) is always the ultimate goal of any digital signal processing (DSP) practitioner. High-order finite impulse response (FIR) filters may meet these requirements when we put no constraint on implementation complexity. In contrast to FIR filters, infinite
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Implementing Moving Average Filters Using Recursion [Tips & Tricks] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Shlomo Engelberg
Moving average filters output the average of N samples, and it is easy to see (and to prove) that they are low-pass filters.
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Sub-Nyquist Coherent Imaging Using an Optimizing Multiplexed Sampling Scheme [Tips & Tricks] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Yeonwoo Jeong, Behnam Tayebi, Jae-Ho Han
Several techniques have been developed to overcome the limitation of sensor bandwidth for 2D signals [1] . Though compressive sensing is an attractive technique that reduces the number of measurements required to record information on a sparse signal basis [2] , [3] , recording information beyond the Nyquist frequency remains difficult when working with nonsparse signals. Given this constraint, this
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Data Science Education: The Signal Processing Perspective [SP Education] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Sharon Gannot, Zheng-Hua Tan, Martin Haardt, Nancy F. Chen, Hoi-To Wai, Ivan Tashev, Walter Kellermann, Justin Dauwels
In the last decade, the signal processing (SP) community has witnessed a paradigm shift from model-based to data-driven methods. Machine learning (ML)—more specifically, deep learning—methodologies are nowadays widely used in all SP fields, e.g., audio, speech, image, video, multimedia, and multimodal/multisensor processing, to name a few. Many data-driven methods also incorporate domain knowledge
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Synthetic Image Detection: Highlights from the IEEE Video and Image Processing Cup 2022 Student Competition [SP Competitions] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-11-08 Davide Cozzolino, Koki Nagano, Lucas Thomaz, Angshul Majumdar, Luisa Verdoliva
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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The Discrete Cosine Transform and Its Impact on Visual Compression: Fifty Years From Its Invention [Perspectives] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Yao Wang, Debargha Mukherjee
Compression is essential for efficient storage and transmission of signals. One powerful method for compression is through the application of orthogonal transforms, which convert a group of ${N}$ data samples into a group of ${N}$ transform coefficients. In transform coding, the ${N}$ samples are first transformed, and then the coefficients are individually quantized and entropy coded into binary bits
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Integrated Sensing and Communications With Reconfigurable Intelligent Surfaces: From signal modeling to processing IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Sundeep Prabhakar Chepuri, Nir Shlezinger, Fan Liu, George C. Alexandropoulos, Stefano Buzzi, Yonina C. Eldar
Integrated sensing and communications (ISAC) are envisioned to be an integral part of future wireless networks, especially when operating at the millimeter-wave (mm-wave) and terahertz (THz) frequency bands. However, establishing wireless connections at these high frequencies is quite challenging, mainly due to the penetrating path loss that prevents reliable communication and sensing. Another emerging
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New Society officers elected [Society News] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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Periodograms and the Method of Averaged Periodograms [Lecture Notes] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Shlomo Engelberg
In this “Lecture Notes” column, we show that it is possible to use deterministic arguments to gain some intuition into why using periodograms without averaging does not work well and why they “fail” in the way they do. We then explain how the probabilistic case can be seen as an extension of the deterministic case. Next, we give a brief description of the method of averaged periodograms and explain
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Synthetic Speech Attribution: Highlights From the IEEE Signal Processing Cup 2022 Student Competition [SP Competitions] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Davide Salvi, Clara Borrelli, Paolo Bestagini, Fabio Antonacci, Matthew Stamm, Lucio Marcenaro, Angshul Majumdar
The possibility of manipulating digital multimedia material is nowadays within everyone’s reach. In the audio case, anybody can create fake synthetic speech tracks using various methods with almost no effort [1] . These methods range from simple waveform concatenation operations to more complex neural networks [2] , [3] .
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SPM Is Your Magazine—You Are Both Reader and Author: Contribute to IEEE Signal Processing Magazine [From the Editor] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Christian Jutten
The objectives of IEEE Signal Processing Magazine ( SPM ) are to propose, for any IEEE Signal Processing Society (SPS) member and beyond, a wide range of tutorial articles on both methods and applications in signal and image processing. The articles are divided into different categories: feature articles, column and forum articles, and articles in special issues, the specificities of which are detailed
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Reflecting on the Successes of ICASSP 2023 [President’s Message] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Athina Petropulu
As we gear up for the International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2024, it is essential to take a moment to celebrate the achievements and highlights of ICASSP 2023, which took place on Rhodes Island, Greece, this past June. ICASSP 2023 was a momentous event as it marked the first postpandemic ICASSP, and the return to in-person meetings. With the theme “Signal Processing
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Election of President-Elect, Regional Directors-at-Large, and Members-at-Large [Society News] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Ahmed Tewfik
Provides society information that may include news, reviews or technical notes that should be of interest to practitioners and researchers.
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On the Concept of Frequency in Signal Processing: A Discussion [Perspectives] IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Moisés Soto-Bajo, Andrés Fraguela Collar, Javier Herrera-Vega
Nikola Tesla said: “If you want to find the secrets of the universe, think in terms of energy, frequency and vibration.” Unfortunately, this is a hieroglyph, and we are still looking for its Rosetta Stone.
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Quaternions in Signal and Image Processing: A comprehensive and objective overview IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Sebastian Miron, Julien Flamant, Nicolas Le Bihan, Pierre Chainais, David Brie
Quaternions are still largely misunderstood and often considered an “exotic” signal representation without much practical utility despite the fact that they have been around the signal and image processing community for more than 30 years now. The main aim of this article is to counter this misconception and to demystify the use of quaternion algebra for solving problems in signal and image processing
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Deep Learning Meets Sparse Regularization: A signal processing perspective IEEE Signal Proc. Mag. (IF 9.4) Pub Date : 2023-09-07 Rahul Parhi, Robert D. Nowak
Deep learning (DL) has been wildly successful in practice, and most of the state-of-the-art machine learning methods are based on neural networks (NNs). Lacking, however, is a rigorous mathematical theory that adequately explains the amazing performance of deep NNs (DNNs). In this article, we present a relatively new mathematical framework that provides the beginning of a deeper understanding of DL