Sentence examples for modulation classifiers are from inspiring English sources

Modulation classifiers are generally divided into two categories.

The weights for the nine modulation band classifiers were obtained using a genetic algorithm that optimized the weights on a small development set.

There are a number of MC methods reported in the literature and most of the current modulation classifiers can be categorized into two main groups: likelihood-based (LB) and feature-based (FB) classifiers [2].

For example, some of the classifiers are designed to handle specific unknown parameters and, to evaluate them, they have considered different types of modulation.

Nonlinear classifiers are more powerful than linear classifiers.

Classifiers are inescapable in Mandarin.

Some different classifiers are empirically compared in order to determine the best classifier.

Two SVM classifiers are proposed.

These weak classifiers are used to construct a strong classifier,.

All three classifiers are more accurate than TSP family classifiers.

The proposed automatic digital modulation classifier can be used for signal recognition in the next generation telecommunication systems, characterized by a flexible and dynamic management of the radio spectrum.