At present, less than 30% of researchers worldwide are women. As an estimate, this number is even lower in the field of Signal Processing, with some sources indicating it could be around 10%. Long-standing biases and gender stereotypes are discouraging girls and women away from science related fields, and STEM research in particular. Science and gender equality are, however, essential to ensure sustainable development as highlighted by UNESCO. In order to change traditional mindsets, gender equality must be promoted, stereotypes defeated, and girls and women should be encouraged to pursue STEM careers. Frontiers in Signal Processing is proud to offer this platform to promote the work of women researchers and engineers, across all areas of Signal Processing. The work presented here highlights the diversity of research performed across the entire breadth of the Signal Processing landscape, and presents advances in theory, experiment and methodology with applications to compelling problems. This article collection is open for submissions across all sections of the journal, and new articles will be added as they are published. Please note: to be considered for this collection, the corresponding author should be a female researcher.

With a novel, less classical approach to the subject, the authors have written a book with the conviction that signal processing should be taught to be fun. The treatment is therefore less focused on the mathematics and more on the conceptual aspects, the idea being to allow the readers to think about the subject at a higher conceptual level, thus building the foundations for more advanced topics. The book remains an engineering text, with the goal of helping students solve real-world problems. In this vein, the last chapter pulls together the individual topics as discussed throughout the book into an in-depth look at the development of an end-to-end communication system, namely, a modem for communicating digital information over an analog channel.

This book provides comprehensive, authoritative surveys covering the modeling, automatic detection, analysis, and synthesis of nonverbal social signals.

This book covers four sections such as artificial intelligence and machine learning; VLSI and signal processing; robotics and automation; and communications and networking. This book is a collection of selected papers presented at the First International Conference on Innovations in Signal Processing and Embedded Systems (ICISPES 2021), organized by MLR Institute of Technology, Hyderabad, India, during October 22–23, 2021. The topics covered are advanced communication technologies, IoT-based systems and applications, application AI in computer vision, natural language processing, reinforcement learning, ANN and deep neural networks, RNN, GAN, CNN and RBM, SOC, NOC design, VLSI and CAD/CAM, cross-layer design, fault tolerance and computation theories, FPGA in outer space, nanotechnology, semiconductor technology, signal and image processing, high-performance computing, pattern recognition and computer vision innovations in robotics, reconfigurable robots, and MEMS/NEMS.

This book presents the select proceedings of the International Conference on Automation, Signal Processing, Instrumentation and Control (i-CASIC) 2020. The book mainly focuses on emerging technologies in electrical systems, IoT-based instrumentation, advanced industrial automation, and advanced image and signal processing. It also includes studies on the analysis, design and implementation of instrumentation systems, and high-accuracy and energy-efficient controllers. The contents of this book will be useful for beginners, researchers as well as professionals interested in instrumentation and control, and other allied fields.

Cognitive Systems and Signal Processing in Image Processing presents different frameworks and applications of cognitive signal processing methods in image processing. This book provides an overview of recent applications in image processing by cognitive signal processing methods in the context of Big Data and Cognitive AI. It presents the amalgamation of cognitive systems and signal processing in the context of image processing approaches in solving various real-word application domains. This book reports the latest progress in cognitive big data and sustainable computing. Various real-time case studies and implemented works are discussed for better understanding and more clarity to readers. The combined model of cognitive data intelligence with learning methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues for computer vision in real-time. - Presents cognitive signal processing methodologies that are related to challenging image processing application domains - Provides the state-of-the-art in cognitive signal processing approaches in the area of big-data image processing - Focuses on other technical aspects and alternatives to traditional tools, algorithms and methodologies - Discusses various real-time case studies and implemented works

Biomedical signal processing in the medical field has helped optimize patient care and diagnosis within medical facilities. As technology in this area continues to advance, it has become imperative to evaluate other ways these computation techniques could be implemented. Computational Tools and Techniques for Biomedical Signal Processing investigates high-performance computing techniques being utilized in hospital information systems. Featuring comprehensive coverage on various theoretical perspectives, best practices, and emergent research in the field, this book is ideally suited for computer scientists, information technologists, biomedical engineers, data-processing specialists, and medical physicists interested in signal processing within medical systems and facilities.