204 search results - page 3 / 41 » Entropy Numbers, Operators and Support Vector Kernels |
FSS
2007
13 years 7 months ago
2007
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
In this paper we address two aspects related to the exploitation of Support Vector Machines (SVM) for classification in real application domains, such as the detection of objects ...
ESANN
2000
13 years 9 months ago
2000
Abstract. This paper proposes a mathematical programming framew ork for combining SVMs with possibly di erent kernels. Compared to single SVMs, the advantage of this approach is tw...
DSD
2004
IEEE
13 years 11 months ago
2004
IEEE
In this paper we present an analysis of the minimal hardware precision required to implement Support Vector Machine (SVM) classification within a Logarithmic Number System archite...
ISCAS
2005
IEEE
14 years 1 months ago
2005
IEEE
—Support Vector Machines are emerging as a powerful machine-learning tool. Logarithmic Number Systems (LNS) utilize the property of logarithmic compression for numerical operatio...