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» Learning to Construct Fast Signal Processing Implementations
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JMLR
2002
117views more  JMLR 2002»
13 years 4 months ago
Learning to Construct Fast Signal Processing Implementations
A single signal processing algorithm can be represented by many mathematically equivalent formulas. However, when these formulas are implemented in code and run on real machines, ...
Bryan Singer, Manuela M. Veloso
ICML
2001
IEEE
14 years 5 months ago
Learning to Generate Fast Signal Processing Implementations
A single signal processing algorithm can be represented by many mathematically equivalent formulas. However, when these formulas are implemented in code and run on real machines, ...
Bryan Singer, Manuela M. Veloso
ISVLSI
2006
IEEE
104views VLSI» more  ISVLSI 2006»
13 years 10 months ago
Adaptive Signal Processing in Mixed-Signal VLSI with Anti-Hebbian Learning
We describe analog and mixed-signal primitives for implementing adaptive signal-processing algorithms in VLSI based on anti-Hebbian learning. Both on-chip calibration techniques a...
Miguel Figueroa, Esteban Matamala, Gonzalo Carvaja...
ICASSP
2011
IEEE
12 years 8 months ago
Fast adaptive variational sparse Bayesian learning with automatic relevance determination
In this work a new adaptive fast variational sparse Bayesian learning (V-SBL) algorithm is proposed that is a variational counterpart of the fast marginal likelihood maximization ...
Dmitriy Shutin, Thomas Buchgraber, Sanjeev R. Kulk...
ICASSP
2011
IEEE
12 years 8 months ago
Versatile and portable DSP platform for learning embedded signal processing
This paper presents a versatile and portable digital signal processing (DSP) platform that is highly suitable for learning embedded signal processing anywhere and anytime. This DS...
Woon-Seng Gan, Abhishek Seth, Sen M. Kuo