| 摘要 |
PROBLEM TO BE SOLVED: To sort the vector categories even when the umber of categories is unknown. SOLUTION: When a vector X is inputted at the time of learning and the vector X belongs to one of existing categories C1 ...Ci , the mean M and a covariance matrixΣare calculated and corrected (5). If the vector X does not belong to any of categories C1 ...Ci , a new category Ci+1 is decided to show M=X andΣ=Σ0 (4). After the learning is over, 'n-variate probability density function f (X)' is calculated based on the M andΣfor the decided category and against the input vector X. Then the category where the value of f (x) is maximized is defined as a category where the vector X belongs (8).
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