Method for Compressed Sensing Using Ultra-low power Analog-to-Digital Conversion

Principal Investigator: Brian Otis

Common approaches to data compression often include Nyquist sampling of the data signal. For data signals with a high degree of redundancy (such as bio-signals, audio and video recording signals), typical data compression methods may be inefficient. Compressed sensing techniques utilize the insight that a sparse signal may be sampled at a much lower rate than the Nyquist rate, and may still be accurately recovered using post-processing in hardware or software. However, available compressed sensing methods provide limited accuracy, low power efficiency, and large circuit size. Therefore, there is an unmet need in both research and industrial settings for efficient and more accurate compressed sensing.

Dr. Allstot and colleagues in the UW Department of Electrical Engineering developed a method and apparatus for compressed sensing analog-to-digital conversion (ADC) integrated circuit. Accordingly, a novel ADC topology is introduced allowing dramatic reduction in the hardware requirement of the ADC. Additionally, using a set of hardware components, 16X power reduction is demonstrated for bio-signal processing. This invention has potential to dramatically improve battery life of portable sensors and devices.

Wireless sensors. Portable scientific instruments. Portable music/video recording devices. Ultra-low power consumption. Reduced integrated circuit size. No need for static random-access memory (SRAM).


For more info, contact: Forest Bohrer

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