Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An important issue in time series classification problems is to find representative prototypes. Especially for roughly segmented time series with spatial distortions, such as human gestures, it is complicated to find templates, which optimally represent signal classes.   present an approach to find optimal time series prototypes in subseries of class templates. Our optimization approach is based on separability measures for prototype candidates and utilizes (but is not limited to) DTW in order to tackle the problem of spatial and temporal distortions. The search for prototypes in the target space is performed by means of a brute force search as ll as an evolution strategy. In our experiments with an artificial dataset  show that brute force search optimization is able to improve the time series classification result and that the application of an evolution strategy yields comparable target function scores while reducing computing time.
['Bastian Hartmann', 'Ingo Schwab', 'Norbert Link']
I am writing a research paper on a idea Prototype Optimization for Temporarily and Spatially Distorted Time Series
[{"from": "human", "value": "I am writing a research paper on a idea Prototype Optimization for Temporarily and Spatially Distorted Time Series"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: An important issue in time series classification problems is to find representative prototypes. Especially for roughly segmented time series with spatial distortions, such as human gestures, it is complicated to find templates, which optimally represent signal classes.   present an approach to find optimal time series prototypes in subseries of class templates. Our optimization approach is based on separability measures for prototype candidates and utilizes (but is not limited to) DTW in order to tackle the problem of spatial and temporal distortions. The search for prototypes in the target space is performed by means of a brute force search as ll as an evolution strategy. In our experiments with an artificial dataset  show that brute force search optimization is able to improve the time series classification result and that the application of an evolution strategy yields comparable target function scores while reducing computing time."}]