This study is concerned with the classification of transient signals that can be represented by piecewise stationary processes.

This paper is concerned with the classification of tran- sient signals which can be represented by piecewise station- ary processes.

Monte Carlo simulations demonstrate that the algorithm for global classification, based on the entire transient, performs better than a classical ...

This paper describes a new approach to this problem based on adaptive pattern recognition employing neural networks and an alternative metric, the Hausdorff ...

Adaptive energy windows and moments of the transformed signals were used as features for classification. Certain classes of transient signals were found for ...

Neural network classifiers have been widely used in classification due to its adaptive and parallel processing ability. This paper concerns classification ...

Classical and most used adaptive algorithms such as the recursive least-squares (RLS) algorithm and the normalized least-mean-square (NLMS) algorithm do not ...

Adaptive energy windows and moments of the transformed signals were used as features for classification. Certain classes of transient signals were found for ...

This method has exhibited a high rate of success for a large set of underwater transients contained in both quiet and noisy ocean environments, and is capable ...

Simulations of detection of a transient with unknown wave shape using these techniques is seen to perform better than classical energy detection. 1.