Introducing overview articles in Signal Processing Transactions [Society News

It will be March when you receive this issue of IEEE Signal Processing Magazine (SPM), and it has been almost four years since the IEEE Signal Processing Society (SPS)'s Inside Signal Processing eNewsletter (eNews) was first launched in April 2007, as the latest addition to SPM. When spring begins, flowers blossom and a new start brings new hopes. As the old Chinese saying goes, “A year's plan starts with spring.” This is precisely what we are doing for the bimonthly SPM and the monthly eNews that complements the magazine.

Each year in spring, the IEEE Signal Processing Society, at the International Conference on Acoustics, Speech, and Signal Processing (ICASSP), presents its annual awards. Several of these awards are related to Best Papers, and although this is not a rule, several of these papers have appeared in IEEE TRANSACTIONS ON SIGNAL PROCESSING. In this editorial, we are pleased to announce the articles receiving 2005 awards. For the 2006 awards, readers are encouraged to nominate candidate papers before September 1, 2006 to the Editor-in-Chief. Nominations will be judged by the relevant Society Technical Committees before being forwarded to the Awards Board.

Throughout the IEEE Signal Processing Society’s (SPS’s) history, conferences have functioned as a main way to connect within the Society, bringing together the signal processing research community to discuss and debate, establish research collaborations, and have a good time. These immersive conference experiences, to which attendees travel from all over the world to be together for a set period of time, have certainly been challenged over these past years, but SPS leadership was able to guide and steer through the constant unanticipated changes, with continued financial stability and growing momentum for a more inclusive future. This article gives an overview of the evolution of SPS conferences in the past decade and presents the challenges ahead.

The IEEE International Symposium on Biomedical Imaging (ISBI) is a scientific conference dedicated to mathematical, algorithmic, and computational aspects of biological and biomedical imaging, across all scales of observation. It fosters knowledge transfer among different imaging communities and contributes to an integrative approach to biomedical imaging. ISBI is a joint initiative from the IEEE Signal Processing Society (SPS) and the IEEE Engineering in Medicine and Biology Society (EMBS). The 2018 meeting will include tutorials, and a scientific program composed of plenary talks, invited special sessions, challenges, as well as oral and poster presentations of peer-reviewed papers. High-quality papers are requested containing original contributions to the topics of interest including image formation and reconstruction, computational and statistical image processing and analysis, dynamic imaging, visualization, image quality assessment, and physical, biological, and statistical modeling. Accepted 4-page regular papers will be published in the symposium proceedings published by IEEE and included in IEEE Xplore. To encourage attendance by a broader audience of imaging scientists and offer additional presentation opportunities, ISBI 2018 will continue to have a second track featuring posters selected from 1-page abstract submissions without subsequent archival publication.

Presents a list of articles published by the IEEE Signal Processing Society (SPS) that ranked among the top 100 most downloaded IEEE Xplore articles.

The annual IEEE 5-Minute Video Clip Contest (5-MICC) was launched by the IEEE Signal Processing Society (SPS), and the selected topic for the competition at IEEE ICIP 2020 was “Fight the Pandemic.” The organizing committee selected three finalist videos and placed them online for public voting. The first one is about a visual analytic system for pandemic management, the second concerns machine learning screening of coronavirus disease (COVID-19) patients based on X-ray images, and the third deals with a COVID-19 test strip reader. Taking the public voting results from more than 800 participants into consideration, the panel of judges decided the final rankings of the three videos. In this article, we present an overview of the 5-MICC at ICIP 2020, describing the competition setup, the teams, and their approaches. We also share our experience and the feedback we received from the finalists.

: The project has successfully demonstrated reduced-rank, space-time equalization for high-speed wireless digital communications capable of reliably transmitting multimedia data in support of military operations in stressful environments involving multipath propagation. Research conducted as part of this effort was recognized by a number of awards including a Technical Achievement Award and a Distinguished Lecturer appointment from the IEEE Signal Processing Society, and two Best Paper Awards from the IEEE Communications Society. A key finding that fueled a number of innovations towards the end of the three-year effort was that adding a stage to the Multi-Stage Wiener Filter was exactly equivalent to taking a step of a Conjugate-Gradient (CG) search. A key innovation was the formulation of the matrix-vector product in the CG algorithm in terms of low-complexity FFT's for reduced computation and storage requirements. The results of this research was published extensively in a number of high-profile IEEE and SPIE conferences.

EDITORIAL article Front. Physiol., 05 November 2012Sec. Computational Physiology and Medicine Volume 3 - 2012 | https://doi.org/10.3389/fphys.2012.00425

Speech technologies have been developed for decades as a typical signal processing area, while the last decade has brought a huge progress based on new machine learning paradigms. Owing not only to their intrinsic complexity but also to their relation with cognitive sciences, speech technologies are now viewed as a prime example of interdisciplinary knowledge area. This review article on speech signal analysis and processing, corresponding machine learning algorithms, and applied computational intelligence aims to give an insight into several fields, covering speech production and auditory perception, cognitive aspects of speech communication and language understanding, both speech recognition and text-to-speech synthesis in more details, and consequently the main directions in development of spoken dialogue systems. Additionally, the article discusses the concepts and recent advances in speech signal compression, coding, and transmission, including cognitive speech coding. To conclude, the main intention of this article is to highlight recent achievements and challenges based on new machine learning paradigms that, over the last decade, had an immense impact in the field of speech signal processing.

Bioacoustic signal processing has emerged as a critical field in biological monitoring, species identification, and ecological assessment. However, the presence of noise poses significant challenges to the accurate analysis of these signals in both terrestrial and aquatic environments. This survey paper provides a comprehensive review of denoising techniques applied to bioacoustic signals across aerial and underwater domains. We systematically categorize and compare traditional signal processing methods, statistical approaches, and modern machine learning techniques. Our analysis reveals that while fundamental principles of signal processing remain consistent across domains, the unique acoustic properties and noise characteristics of air and water necessitate specialized approaches. We further identify key research gaps and propose future directions, including multimodal fusion, adaptive real-time processing, and standardized evaluation frameworks. This survey serves as a resource for researchers and practitioners working at the intersection of signal processing and bioacoustics in diverse environmental contexts.

A wireless multiple-input multiple-output (MIMO) communications transceiver is a promising candidate for next generation wireless systems. It can enhance the capacity and reliability of the communication link. MIMO is enabled by the presence of multiple transmitting antennas and multiple receiving antennas in the communication link. The benefits of MIMO communication are obtained through a combination of antenna arrays, signal processing, and coding algorithms, which adapt the link to the changing channel. In this critical review paper, a propagation-oriented viewpoint is adopted to discuss wireless MIMO. We give an overview of current research areas and discuss some open problems.

Over-complete systems of vectors, or in short, frames, play the role of analog codes in many areas of communication and signal processing. To name a few, spreading sequences for code-division multiple access (CDMA), over-complete representations for multiple-description (MD) source coding, space-time codes, sensing matrices for compressed sensing (CS), and more recently, codes for unreliable distributed computation. In this survey paper we observe an informationtheoretic random-like behavior of frame subsets. Such subframes arise in setups involving erasures (communication), random user activity (multiple access), or sparsity (signal processing), in addition to channel or quantization noise. The goodness of a frame as an analog code is a function of the eigenvalues of a sub-frame, averaged over all subframes (e.g., harmonic mean of the eigenvalues relates to least-square estimation error, while geometric mean to the Shannon transform, and condition number to the restricted isometry property). Within the highly symmetric class of Equiangular Tight Frames (ETF), as well as other “near ETF” families, we show a universal behavior of the empirical eigenvalue distribution (ESD) of a randomly-selected sub-frame: (i) the ESD is asymptotically indistinguishable from Wachter’s MANOVA distribution; and (ii) it exhibits a convergence rate to this limit that is indistinguishable from that of a matrix sequence drawn from MANOVA (Jacobi) ensembles of corresponding dimensions. Some of these results follow from careful statistical analysis of empirical evidence, and some are proved analytically using random matrix theory arguments of independent interest. The goodness measures of the MANOVA limit distribution are better, in a concrete formal sense, than those of the Marchenko–Pastur distribution at the same aspect ratio, implying that deterministic analog codes are better than random (i.i.d.) analog codes. We further give evidence that the ETF (and near ETF) family is in fact superior to any other frame family in terms of its typical sub-frame goodness.

2006 16th IEEE Signal Processing Society Workshop on Machine Learning for Signal Processing

PQR signal quality indexes: A method for real-time photoplethysmogram signal quality estimation based on noise interferences

Cairo, Egypt, will host the 2009 IEEE International Con ference on Image Processing (ICIP) 7-11 November 2009. This is the first time that ICIP will be held in the Middle East and only the second time that any major IEEE Signal Processing Society conference, ICASSP or ICIP, is taking place in this region (the first conference was ICASSP, which took place in Istanbul). ICIP 2009 is one of the main Society initiatives to reach out and have a signal processing global impact.