This book presents the latest achievements in the field of theory and practice of information processing in the CNS SEMS. Recently, the task of integrating computer technologies, transmitting and storing information, monitoring and controlling objects of the physical world has become urgent. This capability is provided by Smart Electromechanical Systems (SEMS) used in Cyber-Physical Systems (CPhS). The main tasks in the field of theory and practice of SEMS are to ensure the efficiency, reliability and safety of functioning in real time. The task of obtaining reliable information about the selection environment, as well as object recognition and identification, is especially important when several SEMS interact in a group. Since in this case, it is necessary to ensure the safety and speed of the planned behavior of all members of the group.

The purpose of the publication is to familiarize with the latest achievements of scientists of the Russian Academy of Sciences and leading universities of Russia in the field of theory and practice of information processing in the CNS of EMS, as well as to familiarize with the development of methods and algorithms for recognition, identification and modeling based on the principles of bionics, adaptivity, intelligence and parallelism in information processing and computing.

Topics of primary interest include, but are not limited to the following:

• Methods and systems of recognition and identification;
• Mathematical and computer modeling;
• Measurement systems to identify the simulation of the selection environment;

• Sensors and auxiliary SEMS systems. This book is intended for students, scientists and engineers specializing in smart electromechanical systems and robotics.

  Inhalt
  Identification of SEMS frequency characteristics using basic functions.- Analysis of Relationships between Problems of Finding Interesting Consequences and Constraints Satisfaction for SEMS Knowledge Bases in the Framework of N -tuple Algebra.- Extended Object Detection: flexible object description system for detection in robotic tasks.- Analysis of energy and noise components of the automatic optoelectronic drone detection system.- Self-Moving Parallel Speleological Robot with Spatial Tactile System of Recognition Contact Surface.- Computer modeling of systems of Logical-Probabilistic Classification of objects in the environment of choice.- Modeling of systems of Logical-Linguistic Classification of images.- Assessment of UAV Intelligence Based on the Results of Computer Modeling.- Assessment of group intelligence SEMS. <p