Low-power and high-quality Cordic-based Loeffler DCT for signal processing

2007 ◽  
Vol 1 (6) ◽  
pp. 453 ◽  
Author(s):  
C.-C. Sun ◽  
S.-J. Ruan ◽  
B. Heyne ◽  
J. Goetze
Keyword(s):  
Signal Processing ◽  
Low Power ◽  
High Quality

scholarly journals Patch-Type Vibration Visualization (PVV) Sensor System Based on Triboelectric Effect

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3976
Author(s):  
Sun Jin Kim ◽  
Myeong-Lok Seol ◽  
Byun-Young Chung ◽  
Dae-Sic Jang ◽  
Jonghwan Kim ◽  
...  
Keyword(s):  
Signal Processing ◽  
Low Power ◽  
Nuclear Power ◽  
Power Plants ◽  
Computing System ◽  
Sensor System ◽  
Wireless Sensor ◽  
Sensor Systems ◽  
Patch Type ◽  
Triboelectric Effect

Self-powered wireless sensor systems have emerged as an important topic for condition monitoring in nuclear power plants. However, commercial wireless sensor systems still cannot be fully self-sustainable due to the high power consumption caused by excessive signal processing in a mini-electronic computing system. In this sense, it is essential not only to integrate the sensor system with energy-harvesting devices but also to develop simple data processing methods for low power schemes. In this paper, we report a patch-type vibration visualization (PVV) sensor system based on the triboelectric effect and a visualization technique for self-sustainable operation. The PVV sensor system composed of a polyethylene terephthalate (PET)/Al/LCD screen directly converts the triboelectric signal into an informative black pattern on the LCD screen without excessive signal processing, enabling extremely low power operation. In addition, a proposed image processing method reconverts the black patterns to frequency and acceleration values through a remote-control camera. With these simple signal-to-pattern conversion and pattern-to-data reconversion techniques, a vibration visualization sensor network has successfully been demonstrated.

Low-Power Digital Signal Processing Using Approximate Adders

2013 ◽  
Vol 32 (1) ◽  
pp. 124-137 ◽  
Author(s):  
Vaibhav Gupta ◽  
Debabrata Mohapatra ◽  
Anand Raghunathan ◽  
Kaushik Roy
Keyword(s):  
Signal Processing ◽  
Digital Signal Processing ◽  
Low Power ◽  
Digital Signal

scholarly journals A Survey on FPGA-Based Sensor Systems: Towards Intelligent and Reconfigurable Low-Power Sensors for Computer Vision, Control and Signal Processing

Sensors ◽  
2014 ◽  
Vol 14 (4) ◽  
pp. 6247-6278 ◽  
Author(s):  
Gabriel García ◽  
Carlos Jara ◽  
Jorge Pomares ◽  
Aiman Alabdo ◽  
Lucas Poggi ◽  
...  
Keyword(s):  
Computer Vision ◽  
Signal Processing ◽  
Low Power ◽  
Sensor Systems ◽  
Vision Control

Synthesis of high-quality monolayer graphene by low-power plasma

2019 ◽  
Vol 19 (1) ◽  
pp. 44-49
Author(s):  
Hyo-Ki Hong ◽  
Na Yeon Kim ◽  
Aram Yoon ◽  
Suk Woo Lee ◽  
Jungmin Park ◽  
...  
Keyword(s):  
Low Power ◽  
Monolayer Graphene ◽  
High Quality
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