As the critical dimensions in semiconductor technologies continue to scale into the nanoscale regime, device speeds are increasing significantly, the supply voltage is decreasing very significantly while the threshold voltage is not being reduced as aggressively. Technology scaling and the associated reduction of the supply voltage leads to a reduction of power consumption for digital ICs while still allowing the clock rate to increase. For analog front-end circuits power supply scaling is becoming a fundamental limitation. These circuits provide the indispensable interface between the analog physical world and the digital signal processing architecture. The reduction of the signal amplitude, due to drastically lower power supplies in nanoscale semiconductors, results in a very significant reduction in the accuracy of the analog circuits. A novel approach is needed for end-to-end signal processing below 1~V. Rather than being limited by the disappearing voltage headroom, the emergence of phenomenal device speeds has to be used. A paradigm shift is in order - instead of encoding information in the amplitude domain, time domain encoding should be employed.
The research investigates a new theoretical foundation for the representation and computation of information in the time domain. Three main research themes are studied: (i) Information Representation and Signal Recovery in the Time Domain, (ii) Computation in the Time Domain, and (iii) Real-Time Algorithms and Robustness.
The research extends the representation of one dimensional time dependent signals to two and three dimensional space-time signals. By adding one or two spatial dimensions, models of speech and video processing inspired by the inner ear and the retina, two of the key natural sensory systems can be explored. The intellectual merit of this project is in devising an unique approach for computation in the time domain that is inspired by models arising in natural sensory systems and is established on sound theoretical foundations of cutting edge mathematical modeling. The broader impacts of the proposed activity include (i) an exploration of the vast potential in the crossroads of neuroscience and nanotechnology, and (ii) an interdisciplinary undergraduate capstone lab project and a graduate level course.
LEVEL OF EFFORT ===============
At the recommended level of support, the PI will make every effort to meet the original scope and level of effort of the project.
