Bitcoin is the most famous digital currency in world and has become an investment asset. Prediction one of important matters market. In economic field, there are different studies on reasons for price change how to predict trend or Therefore, Bitcoin, predicting can effectively help investors. Data from www. Coingecko, bitcoin sorted according time sequence. Using series model, a specific perio...

In this paper statistical and time series models are used for determining the random drift of a dynamically Tuned Gyroscope (DTG). This drift is compensated with optimal predictive transfer function. Also nonlinear neural-network and fuzzy-neural models are investigated for prediction and compensation of the random drift. Finally the different models are compared together and their advantages a...

Several signal processing tools are integrated into machine learning models for performance and computational cost improvements. Fourier transform (FT) its variants, which powerful spectral analysis, employed in the prediction of univariate time series by converting them to sequences domain be processed further recurrent neural networks (RNNs). This approach increases reduces training compared ...

We survey aspects of prediction theory in infinitely many dimensions, with a view to the and applications functional time series.

In today’s day and age, a mobile phone has become basic requirement needed for anyone to thrive. With the cellular traffic demand increasing so dramatically, it is now necessary accurately predict user in networks, improve performance terms of resource allocation utilization. Since learning prediction classical appealing field, which still yields many meaningful results, there been an interest ...