Abstract
This paper explores the similarities of the adaptive filter and the cerebellum for implementing to artificial vision. Worldwide research has shown that adaptive systems are growing field of research; it is an evolutionary process, the progress of which will be an important step in the development of artificial vision control. Also, features of cerebellar inspired control have been investigated by many researchers with a view to implementing it in robotics. Studies show that the cerebellum is a region of the brain strongly associated with adaptive control and skillful motion. Its importance is emphasized by the fact that it contains up to 80% of all neurons in the human brain. These cells are located very evenly in discrete cerebellar microcircuits, which are repeated through the cerebellar cortex. Understanding this algorithm of the cerebellum is a fundamental step towards understanding the biological computations involved in sensorimotor control. The adaptive filter model of the cerebellum microcircuit is used to solve problems of biological motor control, such as vestibulo-ocular reflex (VOR). This adaptive filter is built on the basis of the minimum mean square error method and on the basis of an adaptive system with a reference model. The paper evaluates the performance of a computational model of image stabilization based on the adaptive filter model of the cerebellum (mathematical description).
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Nussibaliyeva, A., Carbone, G., Mussina, A., Balbayev, G. (2019). Study of Artificial Vision on the Adaptive Filter Basis for Implementation in Robotic Systems. In: Uhl, T. (eds) Advances in Mechanism and Machine Science. IFToMM WC 2019. Mechanisms and Machine Science, vol 73. Springer, Cham. https://doi.org/10.1007/978-3-030-20131-9_229
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DOI: https://doi.org/10.1007/978-3-030-20131-9_229
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