The invention of the automobile has transformed how people live, work, and interact in society. How will signal processing advance today’s vehicles into “smart” cars that are able to think and contribute to the task of operating a vehicle? The December 2016 issue of the IEEE Signal Processing Magazine provides a venue for summarizing, educating, and sharing the state of the art in signal processing applied to the domain of automotive systems.

Learn about Ethics and Autonomous Systems in Ronald C. Arkin's article in Proceedings of the IEEE.

The June 2016 special issue of Proceedings of the IEEE addresses the importance of GNSS technology in our life and reflect on its ubiquitous use in service infrastructures. Specifically, it focusses on various types of jammers and analyzes their effects on different processing stages and overall GNSS receiver performance

The idea of representing a signal as a vector living in some linear vector space has borne tremendous fruit in signal processing: this viewpoint provides an encompassing framework for classical least-squares and subspace-based signal processing, and a language with which to model a signal’s structural properties.

Many modern signal processing (SP) methods rely very strongly on probability and statistics tools to solve problems; for example, they use stochastic models to represent the data observation process and the prior knowledge available and they obtain solutions by performing statistical inference (e.g., using maximum likelihood or Bayesian strategies).

Biomedical signals have been widely used in the clinical setting for diagnostics, guiding therapy, patient monitoring, disease prevention, and risk assessment. The special issue of Proceedings of the IEEE in Feb. 2016 comprises 12 reviews that address challenges in applicative biomedical contexts by emphasizing the relevance of the methodological problem, the clinical importance of extracted information, and the possibility for future technological developments.