Journal:Informatica
Volume 25, Issue 2 (2014), pp. 283–298
Abstract
New asymmetric cipher based on matrix power function is presented. Cipher belongs to the class of recently intensively evolving non-commuting cryptography due to expectation of its resistance to potential quantum cryptanalysis.
The algebraic structures for proposed cipher construction are defined. Security analysis was performed and security parameters are defined. On the base of this research the secure parameters values are determined. The comparison of efficiency of microprocessor realization of proposed algorithm with different security parameters values is presented.
Journal:Informatica
Volume 25, Issue 2 (2014), pp. 209–220
Abstract
The paper presents a novel algorithm for restoration of the missing samples in additive Gaussian noise based on the forward–backward autoregressive (AR) parameter estimation approach and the extrapolation technique. The proposed algorithm is implemented in two consecutive steps. In the first step, the forward–backward approach is used to estimate the parameters of the given neighbouring segments, while in the second step the extrapolation technique for the segments is applied to restore the samples of the missing segment. The experimental results demonstrate that the restoration error of the samples of the missing segment using the proposed algorithm is reduced as compared with the Burg algorithm.
Journal:Informatica
Volume 22, Issue 2 (2011), pp. 177–188
Abstract
The paper presents a novel method for improving the estimates of closely-spaced frequencies of a short length signal in additive Gaussian noise based on the Burg algorithm with extrapolation. The proposed method is implemented in two consecutive steps. In the first step, the Burg algorithm is used to estimate the parameters of the predictive filter, while in the second step the extrapolation technique of the signal is used to improve the frequency estimates. The experimental results demonstrate that the frequency estimates of the short length signal, using the Burg algorithm with extrapolation, are more accurate than the frequency estimates using the Burg algorithm without extrapolation.
Journal:Informatica
Volume 14, Issue 3 (2003), pp. 295–322
Abstract
This paper considers an information aspect of the problem of the joint filtering and generalized extrapolation, when the output of observation channels (data transmission) is the realizations set of the processes with continuous and discrete time, which depend on both the current and the past values of unobservable process (useful signal). The relations defining time evolution of Shannon information are obtained. The particular problems of the memory channels information efficiency and optimal transmission of stochastic processes, with applying the general results are considered.
Journal:Informatica
Volume 12, Issue 3 (2001), pp. 455–468
Abstract
This paper describes a preliminary algorithm performing epilepsy prediction by means of visual perception tests and digital electroencephalograph data analysis. Special machine learning algorithm and signal processing method are used. The algorithm is tested on real data of epileptic and healthy persons that are treated in Kaunas Medical University Clinics, Lithuania. The detailed examination of results shows that computerized visual perception testing and automated data analysis could be used for brain damages diagnosing.