Gaussian wavelet features and their applications for analysis of discretized signals Original Research Article

Problems of analysis of symmetric, bell-shaped signals registered in a discrete form are considered. Fast and direct methods for their processing are proposed on the basis of vanishing momentum wavelets. Unlike previous works, wavelets of higher order are used extensively in these methods. A new wavelet feature is observed: the permanence of their relative square. It makes possible to choose an optimal scale coefficient that is common for several wavelet-transforms. Numerical simulations show the high accuracy of proposed algorithms comparable with the more laborious methods of a Gaussian fitting to discrete measurements.