IEEE Signal Processing Magazine

The success of artificial neural networks (ANNs) in carrying out various specialized cognitive tasks has brought renewed efforts to apply machine learning (ML) tools for economic, commercial, and societal aims, while also raising expectations regarding the advent of an artificial “general intelligence” [1]–[2][3]. Recent highly publicized examples of ML breakthroughs include the ANN-based algorithm AlphaGo...

In my September editorial [1], I outlined the important components of good feature articles in response to feedback from our recent IEEE Periodicals Review and Advisory Committee (PRAC) meeting. In this issue's editorial, I discuss the process of organizing a special issue (SI) for IEEE Signal Processing Magazine (SPM). 

Imagine sitting in a room where every individual is able to read every other individual’s mind. Would you lose your mind? We are living in an age where many of us have already surrendered our personal privacy to online interfaces either knowingly or by deceptive means.

Today, many devices (e.g., cars and other vehicles) we operate for various tasks (e.g., to go from place A to place B) are changing: in the past, they were characterized by a body and control actuators that allowed us to perform these tasks. These days, they are not simply passive recipients of our instructions; 

This article examines the problem of interference in automotive radar. Different types of automotive radar as well as mechanisms and characteristics of interference and the effects of interference on radar system performance are described. The interference-to-noise ratio (INR) at the output of a detector is a measure of the susceptibility of a radar to interference. The INR is derived from different types of interfering and victim radars and depends on the location of both as well as parameters such as transmit power, antenna gain, and bandwidth.

The anniversary of a number of significant signal processing algorithms from the 1960s, including the least mean square algorithm and the Kalman filter, provided an opportunity at ICASSP 2019 to reflect on the links between education and innovation. This led ultimately to the proposal of some special sessions as well a panel session that would provide some insight, via a historical perspective, consideration of the current status, and an assessment of the emerging educational future.

The world is moving faster, and signal processing is helping to lead the way, making mobile technologies faster, safer, and more functional on land and even under the sea. At the Massachusetts Institute of Technology (MIT), engineers have created an algorithm that allows autonomous underwater vehicles (AUVs) to weigh the risks and potential rewards of exploring unknown deep-sea sites in real time. 

One of the main items of feedback during our recent IEEE Periodicals Review and Advisory Committee (PRAC) meeting was that IEEE Signal Processing Magazine (SPM) rejected too many feature article white papers as being “out of scope.” In this editorial, I attempt to outline the key features of a good feature article.