Publications News

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.

Memory is one of the three key factors for cognitive dynamic systems. A paper titled A Comprehensive Study of the Past, Present, and Future of Data Deduplication, published in the Proceedings of the IEEE Sep. 2016, provides a comprehensive survey of the state of the art in data deduplication technologies for storage systems, covering key technologies, main applications, open problems, and future research directions.

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).