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Arun Srikanth
Sep 22, 2009, 9:22:13 AM9/22/09
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Dear all,
The control group seminar for this week will be given by saket (Dual degree student under Dr.Shankar narasimhan). The title and the abstract of the talk is attached below.
All control group members are requested to attend.
Title: Dynamic time warping
Abstract: In real life signals are generally misaligned in time due to various reasons like data dropout, different time response of instruments etc. The analysis of such systems becomes difficult because most post processing techniques require the data to be synchronized. Thus there is a need of an optimization algorithm. Dynamic time warping has been used in the area of speech recognition for the recognition of isolated and connected words, signal alignment, motion recognition, finger print analysis and many other areas. DTW has the ability to synchronize two trajectories by appropriately translating, expanding, and contracting localized segments within both trajectories to achieve a minimum distance between the trajectories. It has also been successfully used in pattern matching to find the best match for a data from a database.
My talk would be a tutorial on Dynamic Time Warping. Its applications and improvements over the years and how it can be used in various fields and when it can not be used.
With regards,
S.Arun srikanth.
The control group seminar for this week will be given by saket (Dual degree student under Dr.Shankar narasimhan). The title and the abstract of the talk is attached below.
All control group members are requested to attend.
Title: Dynamic time warping
Abstract: In real life signals are generally misaligned in time due to various reasons like data dropout, different time response of instruments etc. The analysis of such systems becomes difficult because most post processing techniques require the data to be synchronized. Thus there is a need of an optimization algorithm. Dynamic time warping has been used in the area of speech recognition for the recognition of isolated and connected words, signal alignment, motion recognition, finger print analysis and many other areas. DTW has the ability to synchronize two trajectories by appropriately translating, expanding, and contracting localized segments within both trajectories to achieve a minimum distance between the trajectories. It has also been successfully used in pattern matching to find the best match for a data from a database.
My talk would be a tutorial on Dynamic Time Warping. Its applications and improvements over the years and how it can be used in various fields and when it can not be used.
With regards,
S.Arun srikanth.
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