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ICCAD
1995
IEEE
170views Hardware» more  ICCAD 1995»
15 years 5 months ago
Acceleration techniques for dynamic vector compaction
: We present several techniques for accelerating dynamic vector compaction for combinational and sequential circuits. A key feature of all our techniques is that they significantly...
Anand Raghunathan, Srimat T. Chakradhar
IJON
2008
101views more  IJON 2008»
15 years 1 months ago
Learning dynamics and robustness of vector quantization and neural gas
Various alternatives have been developed to improve the Winner-Takes-All (WTA) mechanism in vector quantization, including the Neural Gas (NG). However, the behavior of these algo...
Aree Witoelar, Michael Biehl, Anarta Ghosh, Barbar...
ICANN
2001
Springer
15 years 6 months ago
Learning and Prediction of the Nonlinear Dynamics of Biological Neurons with Support Vector Machines
Based on biological data we examine the ability of Support Vector Machines (SVMs) with gaussian kernels to learn and predict the nonlinear dynamics of single biological neurons. We...
Thomas Frontzek, Thomas Navin Lal, Rolf Eckmiller
116
Voted
IJCNN
2008
IEEE
15 years 8 months ago
Support vector machines and dynamic time warping for time series
— Effective use of support vector machines (SVMs) in classification necessitates the appropriate choice of a kernel. Designing problem specific kernels involves the definition...
Steinn Gudmundsson, Thomas Philip Runarsson, Sven ...
EUROPAR
2009
Springer
15 years 5 months ago
Dynamic Detection of Uniform and Affine Vectors in GPGPU Computations
Abstract. We present a hardware mechanism which dynamically detects uniform and affine vectors used in Graphics Processing Units, to minimize pressure on the register file and redu...
Sylvain Collange, David Defour, Yao Zhang