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Issue No.02 - February (1971 vol.20)
pp: 176-183
An algorithm for the analysis of multivariant data is presented along with some experimental results. The basic idea of the method is to examine the data in many small subregions, and from this determine the number of governing parameters, or intrinsic dimensionality. This intrinsic dimensionality is usually much lower than the dimensionality that is given by the standard Karhunen-Lo?ve technique. An analysis that demonstrates the feasability of this approach is presented.
Data reduction, dimensionality reduction, interactive systems, intrinsic dimensionality, Karhunen-Lo?ve expansion, multivariant data analysis, principal component, stochastic processes.
K. Fukunaga, D.R. Olsen, "An Algorithm for Finding Intrinsic Dimensionality of Data", IEEE Transactions on Computers, vol.20, no. 2, pp. 176-183, February 1971, doi:10.1109/T-C.1971.223208
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