machine learning databases

[Thanos Kehagias]

on the subject of machine learning databases, here is a request. if one
has a pointer to the kind of data i need (see next paragraph),
or if the people setting up databases now would like to consider
including this kind of data, i will be most grateful.

i am looking at the problem of Time Series Classification. in other
words, there is a number of possible sources, each producing a time
series. previous instances of these time series have been observed,
either labelled (supervised learning) or unlabelled (unsupervised
learning). now a new time series is observed and one wants to decide
which source generated it.

there is a lot of algorithms in the literature that do this kind of thing
(i have some of my own, even) and everyone seems to be using their own
example problem and/or dataset. a classical example of this problem
is, of course, phoneme recognition. what i have not been able to find
is some standard datasets to be used for benchmarks (e.g. sonar,
radar signals, EEG, ECG data and so on). i mean the raw time series,
not some kinf of preprocessed data where the whole time series is
reduced to a static features vector. does anyone know of any such data
in the public domain (except speech data)? i think this would be 
a useful benchmark, and the kind of thing that i have not seen in, for 
instance, the uci collection.

		Thanks a lot,

		Thanasis