Acceptance Rate: 26.48% (for the years 2012 to 2025)

Editorial Board

Editor-in-Chief:

Prof. Yuriy S. Shmaliy
IEEE Fellow,
Universidad de Guanajuato,
MEXICO
E-mail: shmaliy@ugto.mx
Profile in Google Scholar



Co-Editor-in-Chief:


Prof. Abdel-Badeeh M. Salem
Professor of Computer Science, Faculty of Computer and Information Sciences,
Ain Shams University, Cairo, Egypt
Member of European Academy of Sciences and Arts, Class VI, Salzburg, Austria
E-mail: absalem@cis.asu.edu.eg
Profile in Google Scholar


Associate Editors:
Prof. Demetri Terzopoulos, (IEEE Fellow, ACM Fellow), University of California, Los Angeles
Prof. Georgios B. Giannakis, (IEEE Fellow), University of Minnesota, USA
Prof. Brian Barsky, (IEEE Fellow), University of Berkeley, USA
Prof. Aggelos Katsaggelos, (IEEE Fellow), Northwestern University, USA
Prof. Michael Wasfy, (IEEE Fellow), University of Central Florida, Orlando, Florida, USA
Prof. Nikolaos Paragios, Ecole Centrale Paris, France
Prof. Nikolaos G. Bourbakis, (IEEE Fellow), Wright State University, USA
Prof. Nathan A Goodman, University of Oklahoma, OK, USA
Prof. Guan Gui Nanjing , University of Posts and Telecomm, Nanjing, Jiangsu, China
Prof. Zaher M Kassas,(IEEE Fellow), The Ohio State University Columbus, OH, USA
Prof. Gitta Kutyniok, Ludwig-Maximilians University, Munich, Germany
Prof. Vito Pascazio, (IEEE Fellow), University Napoli, Napoli, Italy
Prof. Benjamin H Recht, (IEEE Fellow), University of Berkeley Berkeley, CA
Prof. Martin J Wainwright (IEEE Fellow),LIDS/EECS at MIT Cambridge MA, USA
Prof. Alfred M Bruckstein, (IEEE Fellow), Technion International, Haifa, Israel
Prof. Carlos A Busso, (IEEE Fellow), The University of Texas at Dallas Richardson, TX, USA
Prof. Tsung-Hui Chang, (IEEE Fellow), Chinese University of Hong Kong, Shenzhen Guangdong, China
Prof. Yuejie Chi, (IEEE Fellow), Carnegie Mellon University Pittsburgh, PA, USA
Prof. Jinho Choim, (IEEE Fellow), Deakin University, Australia
Prof. James Garrison, (IEEE Fellow), Purdue University, West Lafayette, USA
Prof. Ghassan Alregib, (IEEE Fellow), Georgia Institute of Technology, Atlanta, GA USA
Prof. Todd Coleman, (IEEE Fellow), University of California, San Diego, USA
Prof. Simon Godsill, (IEEE Fellow), University of Cambridge, UK
Prof. Soummya Kar, (IEEE Fellow), Carnegie Mellon University, Pittsburgh, PA, USA
Prof. Lei Xu, (IEEE Fellow), Chinese University of Hong Kong, Hong Kong
Prof. Hisashi Kobayashi, Princeton University, USA
Prof. Cem Goknar, (Fellow IEEE), Isik University, Istanbul, Turkey
Prof. David Donoho, (IEEE Fellow), Stanford University, Stanford, CA, USA
Prof. Gesualdo Scutari, (IEEE Fellow), Purdue University, West Lafayette, IN, USA
Prof. Patrick Naylor, (IEEE Fellow), Imperial College, London, UK
Prof. Mikko Valkama, University of Tampere, Finland
Prof. Peter Gerstoft, (IEEE Fellow), University of California San, CA, USA
Prof. Gerald Matz, Technical University of Wien, Wien, Austria
Prof. Chunyan Miao, Nanyang Technological University, Singapore, Singapore
Prof. Chandra R Murthy, Indian Institute of Science, Bangalore, India
Prof. Gonzalo Seco Granados, (IEEE Fellow), Universitat Autonoma de Barcelona, Spain
Prof. Anthony Man-Cho So, (IEEE Fellow),The Chinese University of Hong Kong, Hong Kong
Prof. Mathias Baumert, (IEEE Fellow),The University of Adelaide, Adelaide, Australia
Prof. Volkan Cevher, (IEEE Fellow),EPFL (Ecole Polytechnique Federale de Lausanne), Lausanne, Switzerland
Prof. Kevin B Englehart, University of New Brunswick Fredericton, Canada
Prof. Yue Gao Fudan, University Yangpu, Shanghai, China
Prof. Roger Woods, Queen's University of Belfast, Belfast, UK
Prof. Vittorio Murino, University of Verona, Italy

Archive

Welcome message from the Editor-in-Chief

On behalf of the Editorial Board, it is my great pleasure to welcome you to WSEAS Transactions on Signal Processing, a leading international journal dedicated to the advancement of signal processing research. Our mission is to disseminate high‑quality, original, and impactful scientific contributions that address theoretical foundations, innovative methodologies, and real‑world applications of signal and image processing. Signal processing continues to play a pivotal role across a broad spectrum of scientific and engineering disciplines, from communications and multimedia systems to biomedical imaging, machine learning, and data analytics. In this rapidly evolving landscape, our journal serves as a rigorous, trusted forum where researchers, practitioners, and educators can share cutting‑edge research that pushes the boundaries of knowledge and fosters interdisciplinary collaboration. We place the highest emphasis on scientific excellence and relevance. Every submission undergoes a thorough peer‑review process to ensure that published work meets the highest standards of scholarship and contributes new understanding to the global research community. We welcome contributions that offer novel theoretical insights, innovative computational techniques, and sophisticated practical solutions to complex signal processing challenges. Our distinguished Editorial Board comprises globally recognized experts who bring a wealth of experience and mentorship to the journal. Their dedication, together with the efforts of our reviewers and authors, is essential to maintaining the journal’s quality and international reputation.Whether you are an established scholar or an emerging researcher, we encourage you to explore our published volumes, submit your best work, and engage with the vibrant community shaping the future of signal processing. Together, we strive to advance knowledge, inspire innovation, and promote research that makes a meaningful impact on science, technology, and society. Thank you for your interest in WSEAS Transactions on Signal Processing. We look forward to your contributions and continued engagement. Best Regards

The Editor-in-Chief

News for our Readers

Pomelli: Pomelli is an experimental artificial intelligence marketing tool developed by Google through Google Labs in collaboration with Google DeepMind. It was introduced around October 2025 as a beta platform designed mainly to help small and medium-sized businesses automate marketing tasks. The basic idea behind Pomelli is to act as an AI marketing assistant that can automatically generate marketing campaigns, social media posts, advertisements, and visual promotional materials with minimal human input. Instead of manually designing marketing content or hiring professional designers and marketing agencies, a business can simply provide its website address to the system. Pomelli then analyzes the website to understand the company’s brand identity, style, and communication tone.

A key innovation in Pomelli is the concept known as “Business DNA.” When a company enters its website URL, the AI system scans the website and extracts key elements that define the brand. These elements include colors used in the website, fonts and typography, logos, images, slogans, the tone of written communication, and general visual style. From this analysis the system creates a structured representation of the company’s brand identity, which is referred to as Business DNA. This internal model allows the AI to generate new marketing materials that remain consistent with the company’s established visual identity and messaging style.

The typical workflow in Pomelli is relatively simple. First, the system analyzes the company’s website and builds the Business DNA profile. Second, it generates marketing ideas or campaign suggestions based on the brand identity and the business sector. Third, it produces ready-to-use marketing assets such as images, advertisements, banners, promotional graphics, and text content for social media platforms. These generated materials are editable, allowing users to adjust colors, text, layout, or imagery before publishing them. The tool integrates both text generation and image generation technologies so that complete promotional materials can be created automatically.

Pomelli includes several important features designed to simplify digital marketing. These features include automatic generation of marketing campaigns, brand-consistent visual content creation, built-in editing tools for text and images, and support for producing assets suitable for different platforms such as social media posts, web advertisements, and email marketing banners. During its experimental phase the tool has been offered as a web-based platform rather than a standalone mobile application. Initially it has been available primarily in a few English-speaking countries, including the United States, Canada, Australia, and New Zealand.

The broader significance of Pomelli lies in its attempt to automate creative marketing tasks through artificial intelligence. Many small companies do not have dedicated marketing departments or professional designers, and tools like Pomelli aim to reduce this barrier by enabling businesses to generate professional marketing materials quickly and cheaply. In this sense the platform functions as an automated marketing assistant capable of performing many tasks traditionally handled by human marketing teams. By combining website analysis, generative AI, and automated brand modeling, Pomelli represents one of Google’s experiments in using artificial intelligence to streamline and partially automate the creative marketing process.

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