Harmonic wavelet transform

About: Harmonic wavelet transform is a research topic. Over the lifetime, 9602 publications have been published within this topic receiving 247336 citations.

A Class of Multivariate Denoising Algorithms Based on Synchrosqueezing

Abstract: Univariate thresholding techniques based on high resolution time-frequency algorithms, such as the synchrosqueezing transform, have emerged as important tools in removing noise from real world data. Low cost multichannel sensor technology has highlighted the need for direct multivariate denoising, and to this end, we introduce a class of multivariate denoising techniques based on the synchrosqueezing transform. This is achieved by partitioning the time-frequency domain so as to identify a set of modulated oscillations common to the constituent data channels within multivariate data, and by employing a modified universal threshold in order to remove noise components, while retaining signal components of interest. This principle is used to introduce both the wavelet and Fourier based multivariate synchrosqueezing denoising algorithms. The performance of the proposed multivariate denoising algorithm is illustrated on both synthetic and real world data.

Analysis of Natural and Artificial Phenomena Using Signal Processing and Fractional Calculus

Abstract: Abstract In this paper we study several natural and man-made complex phenomena in the perspective of dynamical systems. For each class of phenomena, the system outputs are time-series records obtained in identical conditions. The time-series are viewed as manifestations of the system behavior and are processed for analyzing the system dynamics. First, we use the Fourier transform to process the data and we approximate the amplitude spectra by means of power law functions. We interpret the power law parameters as a phenomenological signature of the system dynamics. Second, we adopt the techniques of non-hierarchical clustering and multidimensional scaling to visualize hidden relationships between the complex phenomena. Third, we propose a vector field based analogy to interpret the patterns unveiled by the PL parameters.

Modulation classification of communication signals

Abstract: In this paper we develop a novel algorithm using wavelet transform and pattern recognition to identify the modulation types of the communication signals automatically. Wavelet transform is used to estimate the symbol rate of the received signals in order to discriminate analogue signals from digital ones. Then the key features are extracted to identify the specific modulation type by threshold method. Computer simulation results demonstrate that the performance of the algorithm is efficient at the SNR /spl les/ 15 dB.

Hardware Implementation of Polyphase-Decomposition-Based Wavelet Filters for Power System Harmonics Estimation

Abstract: Computational time and hardware resource are key issues in hardware implementation of any signal-processing algorithm. This paper presents the design and implementation of a polyphase-decomposition-based new architecture of wavelet filter for power system harmonics estimation using discrete wavelet packet transform (DWPT). Usually, DWPT provides coefficients as the output; however, the proposed architecture also includes provision for providing root mean square values directly. The proposed method reduces computational requirements and save memory resources. Xilinx system generator, a higher abstraction level tool, has been used to simulate and implement the proposed scheme on the Xilinx Artix-7 field-programming gate array AC701 board. Performance of the proposed architecture has been validated and compared through hardware cosimulation with variety of synthetic and experimental signals.