Abstract: This paper proposes a new adaptive pulse coupled neural network simplified models. The parameters of the model are not artificially outside interference, the decision by the pixel itself. On this basis, this paper focuses on the use of pulse coupled neural network ignition matrix for the impulse noise detection and location, and clearly pointed out that the study emphasis in the future. Moreover, the noise filtering algorithms have been ported to Field Programmable Gate Array (FPGA) hardware platform for implementation compare to the implementation of software. The implementation of FPGA hardware platform possesses high-speed, reconfiguration and other advantages.
Keywords: Pulse-coupled neural network, Synchronous oscillation, Noise testing.
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Abstract: currently, in Albania, there is an increased interest in data mining and educational system, making educational data misning a new growing research community. Data mining is a powerful tool for academic intervention. Through data mining, a university could, for example, predict which students will or will not graduate. The university can use this information to concentrate on those students that are most at risk. In this paper we attempt to use data mining process to help in enhancing the quality of the higher education system by evaluating student data. For this purpose we have collected data from a public faculty in Tirana from 2011 to 2014, covering 1300 students. The classification process is based on the decision tree as a classification method where the generated rules are studied. We aim to build a system that will facilitate the use of generated rules, which will allow students to predict the average grade of the next year in university.
Keywords: student data, data mining, decision trees, higher education, classification process
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