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» An Adaptive Steganographic Method Using Additive Noise
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KES
2010
Springer
15 years 5 months ago
Evolving takagi sugeno modelling with memory for slow processes
Evolving Takagi Sugeno (eTS) models are optimised for use in applications with high sampling rates. This mode of use produces excellent prediction results very quickly and with lo...
Simon McDonald, Plamen P. Angelov
BMCBI
2010
95views more  BMCBI 2010»
15 years 6 months ago
Identifying main effects and epistatic interactions from large-scale SNP data via adaptive group Lasso
Background: Single nucleotide polymorphism (SNP) based association studies aim at identifying SNPs associated with phenotypes, for example, complex diseases. The associated SNPs m...
Can Yang, Xiang Wan, Qiang Yang, Hong Xue, Weichua...
ICPR
2008
IEEE
16 years 7 months ago
Growing neural gas for temporal clustering
Conventional clustering techniques provide a static snapshot of each vector's commitment to every group. With additive datasets, however, existing methods may not be sufficie...
Isaac J. Sledge, James M. Keller
NECO
2010
103views more  NECO 2010»
15 years 1 months ago
Population Models of Temporal Differentiation
Temporal derivatives are computed by a wide variety of neural circuits, but the problem of performing this computation accurately has received little theoretical study. Here we sy...
Bryan P. Tripp, Chris Eliasmith
ICASSP
2011
IEEE
14 years 10 months ago
Vocal attractiveness of statistical speech synthesisers
Our previous analysis of speaker-adaptive HMM-based speech synthesis methods suggested that there are two possible reasons why average voices can obtain higher subjective scores t...
Sandra Andraszewicz, Junichi Yamagishi, Simon King