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116
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IEEEICCI
2003
IEEE
15 years 9 months ago
Signal Classification through Multifractal Analysis and Complex Domain Neural Networks
This paper describes a system capable of classifying stochastic, self-affine, nonstationary signals produced by nonlinear systems. The classification and analysis of these signals...
Witold Kinsner, V. Cheung, K. Cannons, J. Pear, T....
109
Voted
TIT
2010
96views Education» more  TIT 2010»
14 years 10 months ago
Beyond Nyquist: efficient sampling of sparse bandlimited signals
Wideband analog signals push contemporary analog-to-digital conversion systems to their performance limits. In many applications, however, sampling at the Nyquist rate is inefficie...
Joel A. Tropp, Jason N. Laska, Marco F. Duarte, Ju...
119
Voted
ISLPED
2007
ACM
117views Hardware» more  ISLPED 2007»
15 years 5 months ago
Power signal processing: a new perspective for power analysis and optimization
To address the productivity bottlenecks in power analysis and optimization of modern systems, we propose to treat power as a signal and leverage the rich set of signal processing ...
Quming Zhou, Lin Zhong, Kartik Mohanram
108
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Decomposition of speech signals for analysis of aperiodic components of excitation
The motivation for this study is the need for careful analysis of aperiodicity of the excitation component in expressive voices. The paper proposes analysis methods which can pres...
Bayya Yegnanarayana, Anand Joseph Xavier Medabalim...
118
Voted
GLOBECOM
2008
IEEE
15 years 10 months ago
Information Theoretic Approach to Signal Feature Detection for Cognitive Radio
—Cognitive radio (CR) systems need to be able to adjust the transceiver characteristics in response to stimuli received from the radio environment. Therefore, monitoring the wire...
Mostafa Z. Afgani, Sinan Sinanovic, Harald Haas