The processing of spatial information by the visual system shows a number of similarities to the wavelet transforms that have become popular in applied mathematics. Over the last decade, a range of studies has focused on the question of ‘why’ the visual system would evolve this strategy of coding spatial information. One such approach has focused on the relationship between the visual code and ...

A technology for technical diagnostics based on the multivariate analysis of system status is under consideration. It combines the capabilities of wavelet transforms and relaxation neural networks. Important practical advantages of the proposed technique include the capability to recognise damage using only a few training patterns and the possibility to apply the method for non-stationary input...

Image enhancement plays an important role in computer vision. The degraded image, blurred image and noised image effect the medical diagnosis of image data, satellite image for information retrieval. Various authors and researcher propose a method of image enhancement such as histogram equalization, multi-point histogram equalisation and some method based on neural network and wavelet threshold...

introduction: wavelet transform is one of the useful and suitable tools for time series and signal analysis. nowadays wavelet transform is frequently used in geophysical data processing and interpretation, especially seismic data. however, the use of this method isn’t widespread in gravity and geomagnetic. fedi and quarta (1998), martelet et al. (2001) and de oliveira lyrio (2004) used the wave...

Monthly forecasting of electric energy consumption is important for planning the generation and distribution of power utilities. However, the features of this time series are so complex that directly modeling is difficult. Three kinds of relatively simple series can be derived when a discrete wavelet transform is used to extract the raw features, namely, the rising trend, periodic waves, and st...