The paper presents a new method of conditional combination of quantum systems that takes into account the external environmental conditions. As a practical example of the method presented here, the well-known Bell states are modeled as conditional combination of two q-bits. Analogous approach can be applied in modeling conditional combinations of two and more quantum system sequences.
In the paper, we first present derivation of Heisenberg's uncertainty limit that comes from the non-local Fourier transform. Next we derive a theory yielding into the definition of inner structure of the measuring signal/device that performs resolution beyond Heisenberg's limit. The mathematical theory can be repeated again and again and the computing algorithm can be designed to achieve the predefined resolution precision. At the end of paper, some application examples are introduced.
The paper presents the result of the national ITS project “Monitoring
and control of dangerous goods transport with help of GNSS (Global Navigation Satellite System)” within which the practical pilot trial on different traffic infrastructure is tested. The presented solution relates to routě selection of the dangerous goods transport, so monitoring and control of real movement on selected route is automatically reported.
The definition of the performance parameters, especially accuracy, reliability, dependability are presented. Their estimations are developed by using results from the theory of statistical tolerance intervals in the case of random sample from a normal distribution. The proposed approach is illustrated on two examples.
The paper presents a theory of information systems based on advanced analogies with both classical and quantum physical models. In the first step the information analogies with magneto-electric circuits are introduced and the information parameters are defined under this inspiration. Well-known potential and flow values (e.g. potential and kinetic energy, voltage and electrical current, etc.) are transformed into information values, "information content" and "information flow". In the second step the quantum information models are introduced together with values "wave information flow" and "wave information content". By using these variables, the complex information models are described in more detail together with illustrative examples.
The article presents a new rnethodology concerning the GPS signals
Processing and shows the signál pre-processing the influence on the quality of the prediction error. The next paraineter, which qualified the model quality, is exponential forgetting. For slowly tinie dependent models the exponential forgetting is approximately 0.98 - 0.99. The lower forgetting value points out the time varying model which is not usable for our modelling application. At the end of the article we achieved model for GPS signals with the appropriate prediction errors and with adequate exponential forgetting. AU theoretical results are practically applied on reál GPS signals and the achieved accuracy is much better according to the raw measured data.
Paper presents the results in quantum informatics where two or more quantum subsystems are connected. For modelling the links amongst quantum subsystems the quantum quasi-spin is the most important parameter. We derive a quantum quasi-spin from the condition of logical requirement for the unambiguousness of wave probabilistic function assigned into quantum subsystem. With respect to these results we can define information bosons with integer quasi-spin, information fermions with half-integer quasi-spin and information quarks with third-integer quasi-spin. The methodology can be extended to other variants of quasi-spin.
This paper presents models of quasi-non-ergodic probabilistic systems that are defined through the theory of wave probabilistic functions presented in [10-16]. First of all we show the new methodology on a binary non-ergodic time series. The theory is extended into M-dimensional non-ergodic n-valued systems with linear ergodicity evolution that are called quasi-non-ergodic probabilistic systems. We present two illustrative examples of applications of introduced theories and models.