Described is a system for searching a continuous data stream for exact matches with a priori stored data sequences. The system includes a neural network with an input and an output layer. The input layer has one neuron for each possible character or number in the data stream, and the output layer has one neuron for each stored pattern. Importantly, the delays of the connections from input to output layer are engineered to match the temporal occurrence of an input character within a stored sequence. Thus, if an input sequence has the proper time gaps between characters, matching a stored pattern, then the delayed neural signals result in a simultaneous activation at the receiving neuron, which indicates a detected pattern. For storing a pattern, only one connection for each pair of input character and output neuron has to be specified resulting in sparse coding and quick storage.