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» Discrete Fourier Transform Computation Using Neural Networks
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IEEEICCI
2003
IEEE
15 years 2 months ago
Signal Classification through Multifractal Analysis and Complex Domain Neural Networks
This paper describes a system capable of classifying stochastic, self-affine, nonstationary signals produced by nonlinear systems. The classification and analysis of these signals...
Witold Kinsner, V. Cheung, K. Cannons, J. Pear, T....
PKC
2009
Springer
126views Cryptology» more  PKC 2009»
15 years 10 months ago
Verifiable Rotation of Homomorphic Encryptions
Similar to verifiable shuffling (or, mixing), we consider the problem of verifiable rotating (and random re-encrypting) a given list of homomorphic encryptions. The offset by which...
Sebastiaan de Hoogh, Berry Schoenmakers, Boris Sko...
IJON
2008
152views more  IJON 2008»
14 years 8 months ago
Topos: Spiking neural networks for temporal pattern recognition in complex real sounds
This article depicts the approach used to build the Topos application, a simulation of two-wheel robots able to discern real complex sounds. Topos is framed in the nouvelle concep...
Pablo González-Nalda, Blanca Cases
IPPS
2000
IEEE
15 years 1 months ago
Dynamic Data Layouts for Cache-Conscious Factorization of DFT
Effective utilization of cache memories is a key factor in achieving high performance in computing the Discrete Fourier Transform (DFT). Most optimizationtechniques for computing ...
Neungsoo Park, Dongsoo Kang, Kiran Bondalapati, Vi...
STACS
1999
Springer
15 years 1 months ago
Lower Bounds for Dynamic Algebraic Problems
Abstract. We consider dynamic evaluation of algebraic functions (matrix multiplication, determinant, convolution, Fourier transform, etc.) in the model of Reif and Tate; i.e., if f...
Gudmund Skovbjerg Frandsen, Johan P. Hansen, Peter...