Qualcomm recently opened up the QDSP6 (aka "Hexagon") DSP core in its Snapdragon SoCs to programming access by its customers and software developer partners. Multimedia applications, for example, can benefit from leveraging QDSP6 processing resources, boosting overall performance, minimizing overall power consumption, and freeing up the CPU to tackle other tasks.

The hearing aid is a challenging digital signal processing application. The amount of processing horsepower required is formidable, both to filter out ambient noise and to amplify and otherwise enhance sounds that are of importance, and especially considering that the signal processing chain must be traversed within a few milliseconds in order that the user doesn't perceive lip sync loss or other visual-to-audible delays. But long battery life is equally essential; no hearing aid owner wants to be constantly swapping out power cells.

One of the things I find endlessly fascinating about digital signal processing is that it enables using computation to offset physical limitations. For example, with the right signal processing, you can get awesome sound out of tiny, inexpensive loudspeakers, like those that fit into a smartphone or tablet.

A growing number of products are incorporating computer vision capabilities. This, in turn, has led to rapid growth in the number of processors being offered for vision applications.  Selecting the best processor (whether a chip for use in a system design, or an IP core for use in an SoC) is challenging, for several reasons.

ARM's Cortex-A series of high-performance CPU cores garner significant attention by virtue of their use in high-volume, high-visibility smartphones, tablets, and other consumer electronics devices. But company's Cortex-M and Cortex-R processor families, which target embedded applications, are even more widely used.

Do you ever feel like you could use a bigger brain? One of my all-time favorite Dilbert cartoons is the 1994 strip depicting a consultant so smart he had to "wrap his brain around his torso." In contrast, I often feel as if my brain could benefit from an external accelerator. As an engineer, I've often wondered when humans will be able to boost our brainpower with electronic devices.

BDTI is well known for its software-related capabilities: performance- and power consumption-related benchmarking, for example, along with algorithm evaluation and development and optimization work. In such projects, BDTI frequently employs semiconductor manufacturers' evaluation boards and associated software toolsets, which are often combined to create development kits.

Substantial industry investment in a particular application, both in terms of silicon devices and the software running on and interacting with them, is often a barometer of that application's transition toward mainstream adoption. This has definitely been the case recently for the practical implementation of computer vision technology, which for decades was limited to academic research and niche commercial uses.

Sensory has built its business and made its name over the past 20 years in voice detection and speech recognition, as InsideDSP's April 2013 coverage of the company's TrulyHandsFree always-on voice activation algorithm showcased.

Lately there's been a great deal of buzz about self-driving cars. The idea of autonomous vehicles evokes excitement in some people and terror in others. Clearly, there are significant challenges to be overcome before self-driving cars can become mainstream.