Time delay neural network
Time delay neural network (TDNN)  is a artificial neural network architecture whose primary purpose is to work on sequential data. The TDNN units recognise features independent of time-shift (i.e. sequence position) and usually form part of a larger pattern recognition system. The main application is converting continuous audio into a stream of classified phoneme labels for speech recognition.
An input signal is augmented with delayed copies as other inputs, the neural network is time-shift invariant since it has no internal state.
The original paper presented a perceptron network whose connection weights were trained with the back-propagation algorithm, this may be done in batch or online. The Stuttgart Neural Network Simulator implements that version.
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