Ch. Srinivas^1,*, K. Chandrabhushana Rao²

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1801-1817, 2021, DOI:10.32604/cmc.2021.014981

Abstract In this paper we propose an efficient process of physiological artifact elimination methodology from brain waves (BW), which are also commonly known as electroencephalogram (EEG) signal. In a clinical environment during the acquisition of BW several artifacts contaminates the actual BW component. This leads to inaccurate and ambiguous diagnosis. As the statistical nature of the EEG signal is more non-stationery, adaptive filtering is the more promising method for the process of artifact elimination. In clinical conditions, the conventional adaptive techniques require many numbers of computational operations and leads to data samples overlapping and instability of the algorithm used. This causes… More >

Ridvan Saraçoğlu^*, Ahmet Fatih Kazankaya^†

Computer Systems Science and Engineering, Vol.35, No.1, pp. 13-19, 2020, DOI:10.32604/csse.2020.35.013

Abstract The genetic algorithm (GA) is a metaheuristic method which simulates the life cycle and the survival of the fittest in the nature for solving optimization problems. This study aimed to develop enhanced operation by modifying the current GA. This development process includes an adaptation method that contains certain developments and adds a new process to the classic algorithm. Individuals of a population will be trialed to adapt to the current solution of the problem by taking them separately for each generation. With this adaptation method, it is more likely to get better results in a shorter time. Experimental results show… More >