A RELATIONSHIP BETWEEN COGNITIVE INFORMATION PROCESSING IN LEARNING THEORY AND MACHINE LEARNING TECHNIQUES IN COGNITIVE RADIOS

Authors

  • Zhaneta Tasheva National Military University
  • Rosen Bogdanov National Military University

DOI:

https://doi.org/10.17770/sie2018vol1.3191

Keywords:

Cognitive Information Processing, Cognitive Radio, Cognitive Radio Learning Algorithms, Cognitivism, Learning Theory, Machine Learning

Abstract

The relationship between cognitivism as learning theory in education and machine learning is characterized in this survey paper. The cognitivism describes how learning occurs through internal processing of information and thus leads to understanding and retention. Cognitive information processing plays an active role to understand and process information that learner receives and relates it to already known and stored within learner’s memory. Thus, the cognitive approach defines learning as a change in knowledge which is stored in learner’s memory, and not a change in learner’s behaviour. In regard with importance of various learning problems to designing cognitive communications systems the two main classification categories of learning techniques are explained. Furthermore, the cognitive radio learning algorithms that have been proposed are described. Finally, the similarities and differences among the principles of learning theories and machine learning are discussed.

Author Biographies

  • Zhaneta Tasheva, National Military University
    Department of Computer Systems and Technologies, National Military University,Faculty of Artillery, Air Defense and Communication and Information Systems, ShumenProfessor, D.Sc.
  • Rosen Bogdanov, National Military University
    Department of Communication Networks and Systems, National Military University, Faculty of Artillery, Air Defence and Communication and Information Systems, Shumen, BulgariaAssoc. Prof., PhD.

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Published

2018-05-25