This paper proposes a hybrid modelling approach for forecasting returns and volatilities of the stock market. The model, called ARFIMA-WLLWNN integrates advantages ARFIMA wavelet decomposition technique (namely, discrete MODWT with Daubechies least asymmetric filter) artificial neural network LLWNN network). model develops through two-phase approach. In phase one, improves accuracy network, res...

introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...

An Approach Based On Wavelet Decomposition and Neural Network for ECG Noise

‘Steganography is a art, which enforcing for obscur one part of data or information within another’. this paper shown an image steganography scheme which based on neural network fusion in wavelet transform domain. The cover and stego image is dividing in its frequency coefficients components by wavelet transform domain, and neural network used as classifier. This paper performed on the 256*256 ...