Statistical text language recognition with the use of $n$-gram frequency

Statistical properties of European language texts are investigated with the use of recognition procedure for $n$-gram distribution patterns. The numerical algorithm is constructed for analysis Hurst exponent for letter distance distributions of the text fragment. The accuracy of binary recognition is estimated as 0,99.