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Scott Rickard (SM'06) received his S.B. degree in mathematics in 1992, S.B. degree in computer science and engineering in 1993, and his S.M. degree in electrical engineering and computer science, also in 1993, all from the Massachusetts Institute of Technology. He received the M. A. and Ph. D. degrees in applied and computational mathematics from Princeton University, Princeton, NJ, in 2000 and 2003, respectively.
From 1991 to 1993, he was a research assistant at the Charles Stark Draper Laboratory, MIT, and worked on a prototype analog neural network computer, designed neural networks for mine detection from sonar images, and designed large sets of frequency-hopped waveforms with nearly ideal ambiguity properties for sonar applications. From 1993 to 2003, he was a member of technical staff at Siemens Corporate Research, Princeton. He spent 1995 and 1996 in Munich, Germany, with Siemens, working in the Neural Networks Group. While with Siemens, he developed and applied machine learning technology to industrial problems such as vehicle navigation, automated image analysis, biomedical signal classification, and industrial plant state prediction. He is currently the Director of the Complex & Adaptive Systems Laboratory at University College Dublin, Ireland where he is an Associate Professor of Electronic Engineering. His research for the past several years has focused on the application of time-frequency methods and sparse signal processing for the blind separation of more sources than sensors. His research interests include time-frequency/scale analysis applied to signal processing, blind source separation, computational finance, and Costas arrays.
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论文共 119 篇作者统计合作学者相似作者
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semanticscholar(2013)
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Signal Processingno. 9 (2012): 1961-1969
Declan B Ganter, Fintan J Graham, Martin C Ganter,Scott Rickard,D M Barry, Kevin Jennings, Denis Kozlov
mag(2012)
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