The paper proposes using a fuzzy controller in telecommunication networks for improving the scheduling process. A structure of the fuzzy controller was developed. Linguistic variables, terms and membership functions for input and output values were defined. A rules base was developed. An Adaptive Neuro-fuzzy Inference System (ANFIS) on the base of the fuzzy-controller was developed. A genetic algorithm to improve the rule base was proposed. The operation of ANFIS was simulated and trained.
This paper describes a double compression method (DCM) of biomedical images. A comparison of image compression factors in size JPEG, PNG and developed DCM was carried out. The main purpose of the DCM - compression of medical images while maintaining the key points that carry diagnostic information. To estimate the minimum compression factor an analysis of the coding of random noise image is presented.
The paper deals with a problem of insufficient productivity of existing computer means for large image processing, which do not meet modern requirements posed by resource-intensive computing tasks of laser beam profiling. The research concentrated on one of the profiling problems, namely, real-time processing of spot images of the laser beam profile. Development of a theory of parallel-hierarchic transformation allowed to produce models for high-performance parallel-hierarchical processes, as well as algorithms and software for their implementation based on the GPU-oriented architecture using GPGPU technologies. The analyzed performance of suggested computerized tools for processing and classification of laser beam profile images allows to perform real-time processing of dynamic images of various sizes.