Sentence examples for approaches models the from inspiring English sources

One category of approaches models the mixture STFT coefficients as the product of the source STFT coefficients and complex-valued mixing vectors, which are estimated by frequency-domain independent component analysis (FDICA) [4, 5] or by clustering [6, 7].

In contrast, discriminative approaches model the posterior probabilities directly.

Both direct and indirect approaches model the excitatory synaptic interaction between neighbor principal cells, usually named collateral excitation.

Bayesian approaches, modeling the corrupting noise using a heavy-tailed probality distribution, are proposed in [53, 54].

These approaches model the dependency between graphemes and phonemes and the dependency between phonemes, but do not model dependencies between graphemes [12, 17, 28].

The physically based approaches model the temporal and spatial patterns of APs and meteorological variables [11], which are more accurate than the simple empirical methods.

Information channels: Information-theoretic approaches model the process of translating the genetic code into corresponding amino acids as an error-prone information channel.

Both approaches model the distribution of count data as negative-binomial or Poisson and account for differences between samples in the total number of reads ("library size").

Two further Krogh cylinder approaches modeled the ECS as a porous medium to mimic a densely packed cell population (Abdullah and Das, 2007; Ye et al., 2006).

Graph theory-based approaches model the brain as a complex network, representing it graphically using a collection of nodes and edges.

Regression approaches model the dependence of RNA levels from DNA CN, and consider RNA levels as responses and DNA CN as predictors [ 279].