he Signal Processing Society (SPS) has 12 Technical Committees and 3 Special Interest Groups (SIGs) that support a broad selection of signal processing-related activities defined by the scope of the Society.

So much of our daily lives are powered by signal processing technologies. They go unnoticed mostly because that’s the purpose – to help our lives run more seamlessly, with little to no impact. For example, you’re probably reading this blog on your computer. Guess what? Signal processing is responsible for your computer’s ability to store data and run smoothly.

The deadline for the Regional Director-at-Large Regions 1-6 nominations noted in the below message has been extended to 20 April 2018.  The nomination period for the other noted positions is considered closed.  Submission details are noted below.

If John von Neumann were designing a computer today, there’s no way he would build a thick wall between processing and memory. At least, that’s what computer engineer Naresh Shanbhag of the University of Illinois at Urbana-Champaign believes. 

For centuries, humans have been exploring the subsurface structure of planet Earth. Several Earth geophysical applications, such as mining, earthquake studies, and oil and gas exploration, have driven research that produced, over the years, ground-breaking theories and innovative technologies that image Earth’s subsurface. 

In the coming years, cities are expected to deal with an increasing number and type of services for their citizens, all having to do with overarching goals such as sustainability, environment, quality of life, energy saving, just to name a few. As the population living in urban areas is expected to double by 2050, there is a general consensus that any new process will require more than just an incremental upgrading of the cities’ organization, infrastructure, and services provided to its citizens.

In patent no 9,852,740 a high quality speech is reproduced with a small data amount in speech coding and decoding for performing compression coding and decoding of a speech signal to a digital signal.

Speaker age and gender classification is one of the most challenging problems in speech processing. Recently with developing technologies, identifying a speaker age and gender has become a necessity for speaker verification and identification systems such as identifying suspects in criminal cases, improving human-machine interaction, and adapting music for awaiting people queue.