Cornell University researchers have developed a low-power microchip called \u2018microwave brain\u2019 \u2013 a processor that can compute on both ultrafast data signals and wireless communication signals using the physics of microwaves.<\/p>\n
Integrated fully on a silicon microchip, the processor is regarded as the first-of-its-kind microwave neural network. It computes at a real-time frequency domain for tasks like radio signal decoding, radar target tracking, and digital data processing within 200 milliwatts of power.<\/p>\n
\u201cBecause it\u2019s able to distort in a programmable way across a wide band of frequencies instantaneously, it can be repurposed for several computing tasks,\u201d said lead author Bal Govind, a doctoral student.<\/p>\n
Maxwell Anderson, also a doctoral student, discussed the microchip\u2019s ability to process many signals. \u201cIt bypasses a large number of signal processing steps that digital computers normally have to do,\u201d he said.<\/p>\n
The inner workings<\/p>\n
The chip works like a brain-inspired network; it uses special waveguides to connect its parts to spot patterns and learn from data.<\/p>\n
Unlike the regular digital chips that process instructions step-by-step on a clock, this one uses fast, analogue signals in the microwave range, letting it handle data at tens of gigahertz \u2013 much faster than most digital chips.<\/p>\n
\u201cBal threw away a lot of conventional circuit design to achieve this,\u201d said\u00a0Alyssa Apsel<\/a>, professor of engineering, and a co-senior author.<\/p>\n \u201cInstead of trying to mimic the structure of digital neural networks exactly, he created something that looks more like a controlled mush of frequency behaviors that can ultimately give you high-performance computation,\u201d she continued.<\/p>\n An all-rounder chip<\/p>\n