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New CEVA X baseband architecture takes on multi-RAT

New CEVA X baseband architecture takes on multi-RAT
by Don Dingee on 02-18-2016 at 4:00 pm

What we think of as a “baseband processor” for cellular networks is often comprised of multiple cores. Anecdotes suggest to handle the different signal processing requirements for 2G, 3G, and 4G networks, some SoC designs use three different DSPs plus a control processor such as an ARM core. That’s nuts. What is the point of having… Read More


Low end LTE UE categories seeing more action

Low end LTE UE categories seeing more action
by Don Dingee on 02-08-2016 at 4:00 pm

Most of our attention goes toward the higher end of the LTE UE categories – ones designed for moving large amounts of multimedia data from smartphones and tablets concurrently with voice traffic. An equally interesting discussion is taking shape at the low end of the LTE UE categories targeting M2M and IoT devices with power-efficient,… Read More


Chips on the road to deep learning

Chips on the road to deep learning
by Don Dingee on 01-20-2016 at 7:00 am

CES has been morphing into an automotive show for several years now. Chipmakers were pitching control solutions, infotainment solutions, then connectivity solutions. Phone makers pitched device integration. Automotive electronics suppliers pitched MEMS sensors and cameras. Now, with a lot of pieces in place, the story … Read More


Who Does Voice Recognition in the Samsung Gear S2?

Who Does Voice Recognition in the Samsung Gear S2?
by Eric Esteve on 01-03-2016 at 4:00 pm

If you have bought a Samsung Gear S2 smartwatch for Christmas, you certainly didn’t open it to do a teardown. Chipworks did it and have shared the results: Qualcomm is the big winner here with five different chips: Snapdragon 400 as the main CPU of the system, the RF transceiver, the audio codec, the power and the baseband processor… Read More


DSP gives Project Tango a power dip

DSP gives Project Tango a power dip
by Don Dingee on 12-24-2015 at 12:00 pm

Google’s Project Tango is a prime example of a sophisticated application pushing the boundaries of what is possible within the power envelope of a mobile device. Its objective is to combine 3D motion tracking with depth sensing to understand how a device is moving and gauge its surroundings precisely.… Read More


Low Power LTE for IoT: The Webinar from CEVA

Low Power LTE for IoT: The Webinar from CEVA
by Eric Esteve on 12-13-2015 at 12:00 am

Talking about “connected devices”, we specify any system from high-end smartphones to the simplest low-cost tag, as far as this system will be wirelessly connected. IoT are by definition connected systems, and represent a significant portion of connected devices. By 2020, ABI Research predicts that there will be more than 45… Read More


CEVA Royalty Revenues in 2015 Supports Future IoT Design Win

CEVA Royalty Revenues in 2015 Supports Future IoT Design Win
by Eric Esteve on 12-07-2015 at 7:00 am

DSP IP addressing modem for the mobile phone market is still the flagship product and CEVA enjoys design-win at major semiconductor account (one of them being vertical and also selling the smartphone), but the acquisition of Riviera Waves in 2014 has been a strong sign of diversification. CEVA’ port-folio includes signal processing… Read More


Vector DSP IP charts course for IoT/M2M

Vector DSP IP charts course for IoT/M2M
by Don Dingee on 11-18-2015 at 4:00 pm

For some time, we’ve been talking about ideas for IoT-specific chips, evolved from garden-variety MCUs or mobile SoCs. I sat in on a fascinating talk from an MCU vendor at ARM TechCon 2015 regarding multi-protocol radio silicon, and a question kept coming from the audience: what about software-defined modems? The vague response… Read More


How to Make Smartphone Even Smarter? With Deep Learning

How to Make Smartphone Even Smarter? With Deep Learning
by Majeed Ahmad on 10-26-2015 at 7:00 am

The IT industry marvels like augmented reality and artificial intelligence, which marked technological utopianism in the science fiction movies during the 1970s and 1980s, are here now, enabled by a machine-learning technique called deep learning.… Read More


Convolutional Deep Neural Network is now a reality with CEVA-XM4

Convolutional Deep Neural Network is now a reality with CEVA-XM4
by Eric Esteve on 10-13-2015 at 7:00 am

XM4 DSP has been enriched with CEVA Deep Neural Network (CDNN) Software Framework. Some explanation could be useful before jumping into CDNN. The “Deep” of CDNN comes from “Deep Learning”, a family of neural network methods using high number of layers, so a deep network. The most popular deep learning neural network method is the… Read More