template matching

It is maybe the simplest method for classification, but still with some tricky problem. We can make it powerful and robust by making the template a model instead of a samples set.

1) in DTW, the sample time is a parameter of the model, which can be changed. It has brought great improvement to the effect, and was taken by the Speech Recognition group at the first few years.

2) for spike interference, we can a) use some orthogonality. b) split the template into pieces, d) check the sigma = sum(T-x)^2 . e) make the template a model with its parameter changeable and select the parameter to minimized the sigma, which is the most powerful method.

3) In some way, we can view the HMM as a template model, which can generate a lot of templates of different class.

note : thanks for Akash Kansagra

one of my idea: symbol DTW，feature match as amplitude to use DTW