This paper presents features that characterize power quality disturbances from recorded voltage and current signals using wavelet transformation and S-transform analysis. The disturbance of interest includes sag, swell, transient and harmonics. A 25kv distribution network has been simulated using matlab software. The feature extraction has been done using wavelet transformation and S-transform,...

Within this paper a new feature extraction techniques is presented which uses wavelet analysis and fractal theory for image recognition. The proposed method reduces the dimensionality of a twodimensional pattern by way of a central projection approach, and thereafter, performs Daubechies' wavelet transformation on the derived one-dimensional pattern to generate a set of wavelet transformation s...

Removing divergences in the negative moments of the multi-fractal partition function with the wavelet transformation ABSTRACT We present a promising technique which is capable of accessing the divergence free component of the partition function for the negative moments of the multi-fractal analysis of data using the wavelet transformation. It is based on implicitly bounding the local logarithmi...

A method to recognize planar objects undergoing affine transformation is proposed in this paper. The method is based upon wavelet multiscale features and Hopfield neural networks. The feature vector consists of the multiscale wavelet transformed extremal evolution. The evolution contains the information of the contour primitives in a multiscale manner, which can be used to discriminate dominant...

The design of filtration logic in wavelet transformation is been focused in this paper. The conventional wavelet transformation approaches are observed to be very effective in providing resolution information for each orientation. Though wavelets are been used as a prominent approach for image compression, the accuracy of the image processing is mainly depends on the filters used and their rela...