From the comparative study, it follows that the proposed one is especially effective for improving the characteristic of input signals.
In case of encoding signals with mixed characteristics, one of two coding modes is chosen depending on the characteristic of input contents.
Clustering techniques, which acquire certain characteristics of input data, are efficient methods of extracting knowledge from numerical data sets.
Effects of buried depths, spectrum characteristics of input seismic waves, non-uniform seismic excitation and flexible joints, are thoroughly investigated on seismic responses of the tunnel.
In this paper, we compare the performances of classifier combination methods (bagging, modified random subspace method, classifier selection, parametric fusion) to logistic regression in consideration of various characteristics of input data.
The reason can be found in the unique characteristics of input signal to be encoded, and the application areas of each codec.
The practical PS encoder extracts the inter-channel phase difference (IPD) instead of the ICTD, although ICTD is known to be more reliable than IPD in representing spatial characteristics of input audio [5].
To design a unified speech and audio codec, it is important to fully understand the signal characteristics of input signal as well as the type of distortions related to the codec used, that is, the effect caused by encoding speech signals with audio codec and vice versa.
The number of biclusters, k, however, is arbitrarily specified without considering the inherent characteristics of input data.
A conventional BLSOM performs clustering by means of reflecting the characteristics of input data onto the weight vectors, which are arranged on a two-dimensional lattice in the same format as the input data; that is, characteristics of the input data are summarized and compressed into weight vectors.
