Modeling of Artificial Intelligence

224-228

Authors: A.A.Matskaniuk

The workis aimed atfinding theweightsto ensure an optimuminthe sense of minimumvarianceof measurement errorestimateof the autocorrelation functionof an ergodicstochastic processobservedfor a limited timewhen you usea given formcalculation formula. Achieved at the present time the level of technology made possible the development and wide application of specialized signal processors, used in particular in radar and hydroacoustics to detect air and underwater objects in conditions of strong variability of the environment and object locations. One of the tasks of the new location is the identification of complex and changeable object in terms of interference. There are various methods of identification. In the case of complex statistical object proposed approaches based on the measurement of moments of the distribution of input and output processes of the identifiable object. Thus, the problem arises of measuring points. The result of the measurement is to estimate – an approximate torque value that differs from the true by the amount of the error. The error is a random variable, usually characterized by its expectation and variance. Proposed many methods for the assessment of points, different levels of errors, the complexity of the hardware and/or software implementation, application. Development of new methods is essentially heuristic in nature, is characterized by a diversity of approaches, resulting in difficulties when comparing and choosing the best meets the specified requirements. The following summarises the approach with some common positions to describe a wide class of methods of estimation of the moment of the second order autocorrelation function, find the optimal in sense of minimum of variance of estimation method of its calculation within the restricted class.

238-241

Authors: Yury V. Shornikov

The description of instrumental analysis of hybrid systems (HS) mode with increased rigidity.The algorithm simulation of hybrid systems based on explicit schemes of Runge-Kutta methods. We formulate the general requirements for a modern modeling tool environment HS. On the example of ISMA shows how to implement some of the requirements.

252-262

Authors: Viktor Ya.Tsvetkov

The article organizes information relations. The article explores the implicative, quantitative, qualitative, logical and situational information relations. The article introduces the concept of implicative and situational relations. Article clarifies the definition of information relations. The article describes examples of information relations. The article shows the difference between the information field and information space. The article uses the concept of Aristotle "logical square" to explain the logic of information relations. This work combines scientific fields of linguistics, philosophy, logic, computer science, artificial intelligence.