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Section: Publications & Resources

In this series, we introduce a member of our Society by means of an interview.

Section: Publications & Resources

The IEEE Internet of Things Initiative (IoT) announced it has launched its new IEEE IoT eNewsletter, a bi-monthly online publication highlighting important global IoT-related technology developments, innovations, and trends from the world's top-subject matter experts, researchers, and industry practitioners. The IEEE IoT eNewsletter is provided as a benefit of becoming a member of the complimentary IEEE IoT Technical Community, which anyone actively involved or interested in IoT can join at no charge.

Section: Publications & Resources

The IEEE Signal Processing Society (SPS) announced the 2015 Class of Distinguished Lecturers. Five colleagues were honored and they are: Hynek Hermansky (Johns Hopkins University); Visa Koivunen (Aalto University); Hamid Krim (North Carolina State University); Jean-Christophe Olivo-Marin (Institut Pasteur); and Min Wu (University of Maryland).

Section: Publications & Resources

Precision medicine is a new model of health care which gains insights from an individual's history and biology patterns, to create more precise diagnosis and treatment, at a lower cost. Precision medicine is a big data problem. Despite the completion of Human Genome Project more than ten years ago and the development in the field as a whole, precision medicine is still not a routine practice of medicine due to the lack of appropriate technical work and software platforms.

Section: Publications & Resources

For our December 2014 issue, we cover recent patents granted in the area of image denoising. The section below covers patents granted recently for image de-bluring, enhancement layer video coding,  enhanced MRI signal reconstruction, image noise removal, and anisotropic denoising. An image de-blurring system presented in invention no.

Section: Publications & Resources

In this series, we introduce topics outside of the signal processing world from which we believe signal processing researchers and practitioners can benefit.

Section: Publications & Resources

The Machine Learning for Signal Processing Technical Committee (MLSP TC) is involved with activities that support the use of Machine Learning techniques for Signal Processing problems. The scope of this TC is fairly wide, ranging from traditional machine learning and pattern recognition, to approaches that combine material from both disciplines. Under the scope of the MLSP TC we find areas such as source separation, graphical and kernel methods for time-series, Bayesian non-parametrics, and matrix and tensor factorizations among many more.

Section: Publications & Resources

During the last couple of months, a few new Signal Processing and Machine Learning contests were initiated. Some of the ongoing ones with a strong relation to Signal Processing include: From the domain of Signal Processing for cartography there is a Kaggle contest asking to predict the forest cover type (the predominant kind of tree cover) from strictly cartographic variables (as opposed to remotely sensed data).

Section: Publications & Resources

The signal processing chapter of the IEEE Singapore Section was founded by me in 1989 with over twenty petitioners. It was established first as a special interest group in 1988 and subsequently in 1989 it was upgraded to the chapter status.

Section: Publications & Resources

A team led by Stanford electrical engineers has compressed a completely sequenced human genome to just 2.5 megabytes – small enough to attach to an email. The engineers used what is known as reference-based compression, relying on a human genome sequence that is already known and available. Their compression has improved on the previous record by 37 percent. The genome the team compressed was that of James Watson, who co-discovered the structure of DNA more than 60 years ago