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TSMC
1998
91views more  TSMC 1998»
15 years 6 months ago
Toward the border between neural and Markovian paradigms
— A new tendency in the design of modern signal processing methods is the creation of hybrid algorithms. This paper gives an overview of different signal processing algorithms si...
Piotr Wilinski, Basel Solaiman, A. Hillion, W. Cza...
VLSISP
2002
112views more  VLSISP 2002»
15 years 6 months ago
Minimizing Buffer Requirements under Rate-Optimal Schedule in Regular Dataflow Networks
Large-grain synchronous dataflow graphs or multi-rate graphs have the distinct feature that the nodes of the dataflow graph fire at different rates. Such multi-rate large-grain dat...
Ramaswamy Govindarajan, Guang R. Gao, Palash Desai
BMCBI
2010
113views more  BMCBI 2010»
15 years 6 months ago
Probabilistic Principal Component Analysis for Metabolomic Data
Background: Data from metabolomic studies are typically complex and high-dimensional. Principal component analysis (PCA) is currently the most widely used statistical technique fo...
Gift Nyamundanda, Lorraine Brennan, Isobel Claire ...
NECO
2007
129views more  NECO 2007»
15 years 6 months ago
Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
Shinichi Nakajima, Sumio Watanabe
RAS
2008
135views more  RAS 2008»
15 years 6 months ago
Constructing dependable certainty grids from unreliable sensor data
-- Measurements from sensors as they are used for robotic grid map applications typically show behavior like degradation or discalibration over time, which affects the quality of t...
Wilfried Elmenreich
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