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» Learning to Construct Fast Signal Processing Implementations
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TSP
2010
14 years 8 months ago
Recursive least squares dictionary learning algorithm
We present the Recursive Least Squares Dictionary Learning Algorithm, RLSDLA, which can be used for learning overcomplete dictionaries for sparse signal representation. Most Dicti...
Karl Skretting, Kjersti Engan
ISBI
2008
IEEE
16 years 2 months ago
A spline-based forward model for Optical Diffuse Tomography
Reconstruction algorithms for Optical Diffuse Tomography (ODT) rely heavily on fast and accurate forward models. Arbitrary geometries and boundary conditions need to be handled ri...
Jean-Charles Baritaux, S. Chandra Sekhar, Michael ...
DSD
2006
IEEE
109views Hardware» more  DSD 2006»
15 years 8 months ago
ATOMI II - Framework for Easy Building of Object-oriented Embedded Systems
Traditionally, an embedded system design process demands a considerable amount of expertise, time and money. This makes developing embedded systems difficult for many companies, a...
Tero Vallius, Juha Röning
KDD
2002
ACM
157views Data Mining» more  KDD 2002»
16 years 2 months ago
Learning nonstationary models of normal network traffic for detecting novel attacks
Traditional intrusion detection systems (IDS) detect attacks by comparing current behavior to signatures of known attacks. One main drawback is the inability of detecting new atta...
Matthew V. Mahoney, Philip K. Chan
KDD
2001
ACM
163views Data Mining» more  KDD 2001»
16 years 2 months ago
Learning to recognize brain specific proteins based on low-level features from on-line prediction servers
During the last decade, the area of bioinformatics has produced an overwhelming amount of data, with the recently published draft of the human genome being the most prominent exam...
Henrik Boström, Joakim Cöster, Lars Aske...