Abstract:Artificial neural net models have been studied for years in the hope of achieving human like performance in the field of information processing. In the paper the learning rule of Kohonen self-organizition feature map is modified in order to decrease the fuzziness on the edges of topological neighbours. Then with its associative memory function,we can realize the memory of the features of the input stochastic process, conseqently the detection can be performed. We also describe the mathematical mechanisms of multi-dimentional detection,as its result high-accuracy performance can be derived.