Abstract
The growth of interest in spectral pattern recognition has been stimulated by the need to build instruments that respond to one object or type of object, possibly amid a host of other objects. The needed instruments include analyzers or alarms, medical diagnostic devices such as electroencephalogram or electrocardiogram analyzers, process control devices, and the like. The extra information provided by multivariate (spectral) data is always useful, if not essential, for such difficult tasks. However, the quantity of such data that can be provided by modern instruments requires that statistical pattern recognition techniques be used to extract the useful information from the noise.
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