The paper deals with important issues of diagnosis early signs of diseases of the nervous system, including Parkinson's disease and other specific diseases. Small quantities of violation trajectory of spatial movement of the extremities of human disease at the primary level as the most appropriate features are studied. In modern medical practice is very actual the control the emergence of diseases of the nervous system, including Parkinson's disease. In work a model limbs with six rotational kinematic pairs for diagnosis of early signs of diseases of the nervous system is considered. subject.
The theoretical fundamentals and principles of development models and methods of the production systems development
processes optimization, based on optimal aggregation methodology are proposed. The new approach is a generalization
and development of the methods of maximum and dynamic programming principle. The characteristic feature of the
given approach from its analogues – decomposition of multidimensional optimization problem in one-dimensional tasks
system. On the base of resource links graph analysis between the elements of production systems binary tree of optimal
aggregation is built. As a result, the multidimensional nonlinear model of the production system is replaced with the
equivalent by input-output one-dimensional element, for which variation problem of the optimal development with
integral criterion of the first kind is solved.
Multistage integration of visual information in the brain allows people to respond quickly to most significant stimuli while preserving the ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing, described in this paper, comprises main types of cortical multistage convergence. One of these types occurs within each visual pathway and the other between the pathways. This approach maps input images into a flexible hierarchy which reflects the complexity of the image data. The procedures of temporal image decomposition and hierarchy formation are described in mathematical terms. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image which encapsulates, in a computer manner, structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a very quick response from the system. The result is represented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match.
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