Automatic seismic event tracking using a dynamic time warping algorithm

Automated seismic-to-well ties using dynamic time warping

The quality of seismic-to-well tie is commonly quantified using the classical Pearson’s correlation coefficient. However the seismic wavelet is time-variant, well logging and upscaling is only approximate, and the correlation coefficient does not follow this nonlinear behavior. We introduce the Dynamic Time Warping (DTW) to automate the tying process, accounting for frequency and time variance....

Robot Arm Performing Writing through Speech Recognition Using Dynamic Time Warping Algorithm

This paper aims to develop a writing robot by recognizing the speech signal from the user. The robot arm constructed mainly for the disabled people who can’t perform writing on their own. Here, dynamic time warping (DTW) algorithm is used to recognize the speech signal from the user. The action performed by the robot arm in the environment is done by reducing the redundancy which frequently fac...

Dynamic Time Warping Algorithm Review

Pairwise dynamic time warping for event data

A new version of dynamic time warping for samples of observed event times that are modeled as time-warped intensity processes is introduced. The approach is developed within a framework where for each experimental unit or subject in a sample, a random number of event times or random locations can be observed. As in this setting the number of observed events differs from subject to subject, usua...

Automatic classification of killer whale vocalizations using dynamic time warping.

A set of killer whale sounds from Marineland were recently classified automatically [Brown et al., J. Acoust. Soc. Am. 119, EL34-EL40 (2006)] into call types using dynamic time warping (DTW), multidimensional scaling, and kmeans clustering to give near-perfect agreement with a perceptual classification. Here the effectiveness of four DTW algorithms on a larger and much more challenging set of c...