Skip to main content

Advertisement

Springer Nature is making Coronavirus research free. View research | View latest news | Sign up for updates

Figure 2 | EURASIP Journal on Advances in Signal Processing

Figure 2

From: Discriminant non-stationary signal features’ clustering using hard and fuzzy cluster labeling

Figure 2

The block diagram of our proposed method for discriminant feature clustering. In Stage 1, a set of clusters is identified using an unsupervised clustering method which is simultaneously applied to the training feature vectors extracted from the different classes. In Stage 2, based on the distribution of the train signals in each cluster, it will be decided whether a cluster is normal or abnormal. In the test stage, the class label of each signal is assigned based on the membership of the relying feature vectors to one of these clusters.

Back to article page