The Truncated Fourier Transform (tft) is a variation of the Discrete Fourier Transform (dft/fft) that allows for input vectors that do not have length 2 n for n a positive integer. We present the univariate version of the tft, originally due to Joris van der Hoeven, heavily illustrating the presentation in order to make these methods accessible to a broader audience.

We test various features for recognition of leaves of wooden species. We compare Fourier descriptors, Zernike moments, Legendre moments and Chebyshev moments. All the features are computed from the leaf boundary only. Experimental evaluation on real data indicates that Fourier descriptors slightly outperform the other tested features.

To date, a number of numerical methods, including the popular Finite-Difference Time Domain (FDTD) technique, have been proposed to simulate Ground-Penetrating Radar (GPR) responses. Despite having a number of advantages, the finite-difference method also has pitfalls such as being very time consuming in simulating the most common case of media with high dielectric permittivity, causing the for...

Per temporal frequency component, the (least squares) Parabo-lic Radon Transform (PRT) is equivalent to the (least squares) Nonuniform Discrete Fourier Transform (NDFT). This can be used in two ways. Firstly, the efficiency of the PRT can be improved by using very fast algorithms for the calculation of the direct nonuniform Fourier transform. Secondly, comparing the PRT to the NDFT provides use...

Power quality (PQ) is an issue that is becoming increasingly important to electricity consumers at all levels of usage. Improvement of PQ has a positive impact on sustain profitability of the distribution utility on the one hand and customer satisfaction on the other. To improve the power quality problems, the detection of PQ disturbances should be carried out first. The PQ problems vary in a w...

An image resolution enhancement technique based on interpolation of the high frequency subband images obtained by discrete wavelet transform (DWT) and the input image. The edges are enhanced by introducing an intermediate stage by using stationary wavelet transform (SWT). DWT is applied in order to decompose an input image into different subbands. Then the high frequency subbands as well as the...

Fast algorithms for a wide class of non–separable n–dimensional (nD) discrete unitary K– transforms (DKT) are introduced. They need less 1D DKTs than in the case of the classical radix–2 FFT–type approach. The method utilizes a decomposition of the nDK–transform into the product of a new nD discrete Radon transform and of a set of parallel/independ 1D K–transforms. If the nD K–transform has a s...

Anomaly Detection (AD) has recently become an important application of hyperspectral images analysis. The goal of these algorithms is to find the objects in the image scene which are anomalous in comparison to their surrounding background. One way to improve the performance and runtime of these algorithms is to use Dimensionality Reduction (DR) techniques. This paper evaluates the effect of thr...

Recently, regime shifts or structure breaks had acquired very high attention in analyzing financial time series data. Abrupt of changes in the government policy, financial crises and many of challenges lead to change in the behavior of the financial time series data. In addition, wavelet transform also becomes very famous in the financial sector and it has better advantages than the other filte...