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Comparative analysis of Recurrent and Finite Impulse Response Neural Networks in Time Series Prediction Author

The purpose of this paper is to perform evaluation of two different neural network architectures used for solving temporal problems, i.e. time series prediction. The data sets in this project include Mackey-Glass, Sunspots, and Standard & Poor's 500, the stock market index. The study also presents a comparison study on the two networks and their performance.