Predicting future behavior of chaotic time series system is a challenging area in the literature of nonlinear systems. The prediction's accuracy of chaotic time series is extremely dependent on the model and the learning algorithm. On the other hand the cyclic solar activity as one of the natural chaotic systems has significant effects on earth, climate, satellites and space missions. Several m...

This paper addresses the problem of the estimation of unknown time-varying delays of discrete-time systems. The problem is reformulated as a mode detection for hybrid systems with a switching law depending on the unknown delay. Some existing data-based residual methods used for the estimation of the mode of switching linear discrete-time systems are briefly reviewed and presented in a unified w...

Can a neural network trained by the time series of system A be used to predict evolution B? This problem, knowing as transfer learning in broad sense, is great importance machine and data mining, yet has not been addressed for chaotic systems. Here we investigate systems from perspective synchronization-based state inference, which reservoir computer infer unmeasured variables B, while differen...

The study of the dynamic behavior of a rigid body with one fixed point (gyroscope) has a long history. A number of famous mathematicians and mechanical engineers have devoted enormous time and effort to clarify the role of dynamic effects on its movement (behavior) – stable, periodic, quasi-periodic or chaotic. The main objectives of this review are: 1) to outline the characteristic features of...

Secure communication using synchronization between chaotic systems(chaotic secure communication, for short) is a new concept of secure communication. The great potentials of this kind of “hardware key” secure communication systems had driven the progress of this field rapidly. Since 1992, chaotic secure communication had evolved four generations. In this paper, a detailed history of chaotic sec...