G Enerative Networks as Inverse Problems with S Cattering Transforms

Measurement of Plain Weave Fabrics Density Using Fourier Transforms

Warp and weft spacing and its coefficient of variation affect the physical properties of fabrics such as fabric hand, frictional and mechanical properties. In this paper the weft and warp spacing and its coefficient of variation for plain weave is calculated using Fourier transforms. Different methods have been used in this work including autocorrelation function. First, two dimensional power s...

Forecasting Stock Market Using Wavelet Transforms and Neural Networks and ARIMA (Case study of price index of Tehran Stock Exchange)

The goal of this research is to predict total stock market index of Tehran Stock Exchange, using the compound method of ARIMA and neural network in order for the active participations of finance market as well as macro decision makers to be able to predict trend of the market. First, the series of price index was decomposed by wavelet transform, then the smooth's series  predicted by using...

Numerical Solution of Volterra-Fredholm Integral Equations with The Help of Inverse and Direct Discrete Fuzzy Transforms and Collocation Technique

Measurement of Plain Weave Fabrics Density Using Fourier Transforms

Warp and weft spacing and its coefficient of variation affect the physical properties of fabrics such as fabric hand, frictional and mechanical properties. In this paper the weft and warp spacing and its coefficient of variation for plain weave is calculated using Fourier transforms. Different methods have been used in this work including autocorrelation function. First, two dimensional power s...

Iclr 2018 S Pectral N Ormalization for G Enerative a Dversarial N Etworks

One of the challenges in the study of generative adversarial networks is the instability of its training. In this paper, we propose a novel weight normalization technique called spectral normalization to stabilize the training of the discriminator. Our new normalization technique is computationally light and easy to incorporate into existing implementations. We tested the efficacy of spectral n...