Sentence examples for multiple correlated sources from inspiring English sources

In general, for the state-of-the-art methods we consider, experimental results suggest that introducing multiple correlated sources does not necessarily aid in the recovery performance, while under different scenarios, the aggregation of multiple sources may also introduce prohibitively large communication overheads.

Wireless communication of multiple correlated information sources to a common receiver has become an important research problem due to potential applications in emerging information gathering systems such as wireless sensor networks (WSNs)[1].

In this paper, we develop accurate distortion models for the lossy transmission of two correlated sources in a multiple access Rayleigh fading channel.

Separate source and channel coding is known to be sub-optimal for communicating correlated sources over a Gaussian multiple access channel (GMAC).

Bedini et al.[18] have developed algorithms for the separation of correlated sources found in astrophysical applications based on multiple-lag data covariance matrices, i.e. by exploiting the time structure of sources.

For instance, information from multiple correlated traits could help infer potential sub-groupings when the source of internal dependencies is unknown.

This is particularly an issue in cases with multiple correlated exposures, where the direction of bias is uncertain.

The KLE for multiple correlated random excitations relies on expansions in terms of correlated sets of random variables reflecting the cross-covariance of the random processes.

The proposed metrics are applicable to validation for models with multiple correlated responses.

We consider regression models with multiple correlated responses for each design point.

For totally correlated sources, its modulus reaches 1.