this invention identifies anomalies in a data stream , without prior training , by measuring the difficulty in finding similarities between neighborhoods in the ordered sequence of elements . data elements in an area that is similar to much of the rest of the scene score low mismatches . on the other hand a region that possesses many dissimilarities with other parts of the ordered sequence will attract a high score of mismatches . the invention makes use of a trial and error process to find dissimilarities between parts of the data stream and does not require prior knowledge of the nature of the anomalies that may be present . the method avoids the use of processing dependencies between data elements and is capable of a straightforward parallel implementation for each data element . the invention is of application in searching for anomalous patterns in data streams , which include audio signals , health screening and geographical data . a method of error correction is also described .