The Signal Processing Theory and Methods (SPTM) TC reports on the 2015 Signal Processing/Signal Processing Education Workshop and new TC members

This Funding Opportunity Announcement (FOA) seeks applications that propose research studies that extend experimental protocols beyond the range of acoustic psychophysical research studies widely performed today. This will require design of algorithms and research studies that validate the potential benefits from these novel approaches to acoustic signal processing.

The special issue of the Proceedings of the IEEE in July is the second issue focusing on reconfigurable systems. In the first special issue (vol. 103, no. 3, 2015) introduced by eNewsletter in June, the foundational concepts are addressed. In this special issue, the editors focus on the basic concepts discussed in the first issue by considering more advanced applications, the extension of reconfigurability to other phenomenologies/domains, and the impacts of selected emerging technologies.

The Design and Implementation of Signal Processing Systems Technical Committee (DISPS TC) has the mission to promote and support activities of the IEEE Signal Processing Society in the areas of: i) design, development and implementation of signal processing systems; ii) design of algorithms with implementation in mind and iii) design of software tools and methodologies to support the design of signal processing systems.

Machine learning, a subfield of computer science, has been widely applied in many areas from science to engineering to many interdisciplinary fields. Nature Reviews Genetics recently published an article that summarized machine learning applications in genetics and genomics, authored by University of Washington researchers Maxwell W. Libbrecht and William Stafford Noble. The topics of interest included supervised versus unsupervised learning, generative versus discriminative modeling, incorporating prior knowledge, handling heterogeneous data, feature selection, imbalanced class sizes, handling missing data, and modelling dependence among examples.

The latest IEEE Biometrics Council (BMC) newsletter reports a welcome message from Venu Govindaraju, the new president of the IEEE BMC, latest datasets for fingerprint algorithm evaluation and a large biometrics-based human identification initiative in India.

How fast is online learning evolving? Are wind turbines a promising investment? And how long before a cheap hoverboard makes it to market? Attempting to answer such questions requires knowing something about the rate at which a technology is improving. Now engineers at MIT have devised a formula for estimating how fast a technology is advancing, based on information gleaned from relevant patents.

In our "What should we learn from... " series we report on a special issue from IEEE Potentials in March/April 2015. It gave some interesting comments on Biomimicry or Bioinspiration covering fields such as sensors networks, vision systems, health care and robot design which we believe are very relevant to the signal processing community.