1. A feature pattern recognition system for deciding whether or not one of multiple types of known feature patterns that are found in advance and similar to each other or a new feature pattern that is similar to the known feature pattern is included in a sequence constructed with a finite number of discrete symbols, a segment thereof, or a test segment extracted from the sequence or the segment, comprising: symbol-frequency table storage means for storing a symbol-frequency table generated by obtaining a symbol frequency for each of multiple types of the discrete symbols at each of sequence positions in the feature patterns by using the multiple types of known feature patterns and by corresponding the symbol frequencies to the sequence positions and the types of the discrete symbols in the feature patterns; separation matrix storage means for storing a separation matrix, as a matrix for performing inverse transformation of a basis matrix including feature elements representing the feature patterns, generated by converting to numerals the multiple types of known feature patterns and the multiple types of non-feature patterns that are different from the known feature patterns according to the sequence positions and the types of the discrete symbols by using the symbol-frequency table, by binding the numerals to generate a training data matrix, and by performing an independent component analysis or a principal component analysis by using the training data matrix; test data generating means for generating test data by converting to numerals the to-be-decided sequence, the segment thereof, or the test segment extracted from the sequence or the segment according to the sequence positions and the types of the discrete symbols by using the symbol-frequency table stored in the symbol-frequency table storage means; separation processing means for obtaining separation data or a separation data matrix in which a plurality of the separation data are bound by performing a matrix calculation of multiplying the separation matrix stored in the separation matrix storage means with the test data or a test data matrix in which a plurality of the test data are bound; and decision means for deciding whether or not one of the multiple types of the known feature patterns or the new feature pattern similar to the known feature patterns is included in the to-be-decided sequence, the segment thereof, or the test segment extracted from the sequence or the segment or deciding a degree of existence thereof by using values of feature decision elements assigned according to internal-matrix positions of the feature elements included in the basis matrix among elements constituting the separation data or the separation data matrix obtained by the separation processing means.