3 accepted papers
In the age of Internet of Things (IoT), embedded devices ranging from ARM Cortex M0s with hundreds of KB of RAM to Arduinos with 2KB RAM are expected to perform increasingly sophisticated classification tasks, such as voice and gesture recognition, activity tracking, and biometric security. While co…
We present the concept of logarithmic computation for neural networks. We explore how logarithmic encoding of non-uniformly distributed weights and activations is preferred over linear encoding at resolutions of 4 bits and less. Logarithmic encoding enables networks to 1) achieve higher classificati…
Ultrasound imagers suffer from a large data rate between their analog to digital converter (ADC) front-end and digital beamforming backend. This becomes a limiting factor when the number of elements is increased, such as in modern 2D transducers. To address this issue, prior work considered sub-Nyqu…