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Processing Energy and Signals by Molecular and Supramolecular Systems
Chemistry – A European Journal, 2007AbstractAny kind of device or machine requires a substrate, energy, and information signals. If we wish to operate at the nanometer scale, we must use molecules as substrates. Energy‐ and signal‐processing at a molecular level relies on cause/effect relationships between the input supplied and the kind of process obtained.
BALZANI, VINCENZO +2 more
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Energy efficient Digital Signal Processing
2010 53rd IEEE International Midwest Symposium on Circuits and Systems, 2010This paper focuses on issues related to energy efficient Digital Signal Processing (DSP) - taking a Systems-to-Silicon approach. This implies that achieving maximum energy efficiency in a DSP system is a distributed task from the systems level (compilers, algorithm design etc.) to a silicon (transistor, process technologies etc.) level.
Neeraj Magotra, Jim Larimer
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Circuits for energy harvesting sensor signal processing
2006 43rd ACM/IEEE Design Automation Conference, 2006The recent explosion in capability of embedded and portable electronics has not been matched by battery technology. The slow growth of battery energy density has limited device lifetime and added weight and volume. Passive energy harvesting from solar radiation, thermal sources, or mechanical vibration has potentially wide application in wearable and ...
Rajeevan Amirtharajah +4 more
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Energy-efficient signal processing in wearable embedded systems
Proceedings of the 2012 ACM/IEEE international symposium on Low power electronics and design, 2012Many wearable embedded systems benefit from classification algorithms where statistical features extracted from physiological signals are mapped onto different user's states such as health status of a patient or type of activity performed by a subject.
Hassan Ghasemzadeh +2 more
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Energy-efficient soft error-tolerant digital signal processing
IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2006In this paper, we present energy-efficient soft error-tolerant techniques for digital signal processing (DSP) systems. The proposed technique, referred to as algorithmic soft error-tolerance (ASET), employs low-complexity estimators of a main DSP block to achieve reliable operation in the presence of soft errors.
null Byonghyo Shim, N.R. Shanbhag
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Energy Efficient Biomedical Signal Processing in Implantable Devices
Advances in Science and Technology, 2008Implantable cardiac devices have very strict restrictions on energy dissipation since battery change requires surgery. Today the battery longevity of pacemakers during standard use is up to 10 years which might seem sufficient. However, new functionality is constantly being introduced requiring more advanced signal processing algorithms which in turn ...
Viktor Öwall +2 more
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Energy-efficient soft error-tolerant digital signal processing
The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003, 2004In this paper, we present energy-efficient soft error (SE)-tolerant techniques for digital signal processing (DSP) systems. The proposed technique, referred to as algorithmic soft error-tolerance (ASET), employs an low-complexity estimator of a main DSP block to guarantee reliability in presence of soft errors either in the MDSP or the estimator.
B. Shim, N.R. Shanbhag, S. Lee
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Speech coding for energy-efficient digital signal processing
Proceedings of the 43rd IEEE Midwest Symposium on Circuits and Systems (Cat.No.CH37144), 2000Waveform coding techniques known from low bitrate communication are evaluated for their usefulness in low-power digital filtering of speech signals as used in hearing aids or mobile communication applications. Experimental results are presented to quantify potential power savings subject to statistical signal properties and operating conditions ...
J. Wassner +3 more
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Energy-efficient signal processing via algorithmic noise-tolerance
Proceedings of the 1999 international symposium on Low power electronics and design - ISLPED '99, 1999In this paper, we propose a framework for low-energy digital signal processing (DSP) where the supply voltage is scaled beyond the critical voltage required to match the critical path delay to the throughput. This deliberate introduction of input-dependent errors leads to degradation in the algorithmic performance, which is compensated for via ...
R. Hegde, N.R. Shanbhag
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Reliable and energy-efficient digital signal processing
Proceedings of the 39th conference on Design automation - DAC '02, 2002This paper provides an overview of algorithmic noise-tolerance (ANT) for designing reliable and energy-efficient digital signal processing systems. Techniques such as prediction-based, error cancellation-based, and reduced precision redundancy based ANT are discussed. Average energy-savings range from 67% to 71% over conventional systems. Fluid IP core
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