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The paper presents research results on predicting the Polish Timescale UTC(PL) by the means of GMDH-type neural network and linear regression method for data prepared in the form of time series built on the basis of [UTC - UTC(PL)] and [UTCr - UTC(PL)] deviations and values of a phase time from UTC(PL). The obtained results show comparable prediction quality by means of GMDH-type neural network with prepared procedure of predicting and linear regression method modified by the author for timescale characterized with high stability.
W pracy przedstawiono wyniki badań nad prognozowaniem Polskiej Skali Czasu UTC(PL) przy zastosowaniu sieci neuronowej typu GMDH oraz metody regresji liniowej dla danych przygotowanych w formie szeregu czasowego, zbudowanego z wartości odchyleń [UTC - UTC(PL)] oraz [UTCr - UTC(PL)] oraz wartości czasu fazowego z UTC(PL). Wyniki badań pokazały porównywalną jakość prognozowania z zastosowaniem sieci neuronowej typu GMDH i opracowanej procedury prognozowania oraz zmodyfikowanej przez autora metody regresji liniowej w przypadku skali czasu charakteryzującej się dużą stabilnością.
Authentication based on handwritten signature is one of the most accepted authentication systems based on biometry. In this paper a method for the automatic verification of on-line handwritten signatures using three similarity measures is described. The proposed approach, is based on extreme values and dynamic features of the signature. In investigations proposed coefficients together with the factor [R2] were connected and new signature recognition quality has been achieved.
The handwritten signature is often used for the identity confirmation. From the specialized graphic tablet, we receive the information in form of time strings. In this paper, the research results are presented which refer to the effect of applying the method of point detection of the highest curvature. Signatures are normalized by means of a DTW method, where two time strings representing the signature features are matched.
Nowadays, automatic signature verification is an active area of researches in numerous applications such as bank check verification, access restriction or special areas such as police investigations. In our researches signature was captured by Topaz SigLite T-LBK750-HSB device, where some dynamic features of signature can be also registered. In many transactions, the electronic verification of a person's identity is beneficial, hence it inspires the development of a wide range of automatic identification systems. In this paper the system that automatically authenticates documents based on the owner's handwritten signature is presented.
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