Spectrum Analysis of Nearest Neighbor Signal Using Wigner-Ville Distribution

Volume 5 Issue 1 January - March 2017

Research Paper

Spectrum Analysis of Nearest Neighbor Signal Using Wigner-Ville Distribution

C. Mounika*

PG Scholar, Department of Electronics and Communication Engineering, Sree Vidyanikethan Engineering College, Tirupati, India.

Mounika C. (2017). Spectrum Analysis of Nearest Neighbor Signal Using Wigner-Ville Distribution. i-manager’s Journal on Digital Signal Processing, 5(1), 13-17. https://doi.org/10.26634/jdp.5.1.13527

Abstract

One of the most powerful tools for the representation of the classical signal processing methods is algebraic structure. Algebraic Signal Processing (ASP) provides a whole frame for representing the classical signal processing concepts. In ASP, the signal model is defined as a triple (A, M, Φ), where A is a chosen algebra filters, M is an associated A -module of signals, and Φ generalizes the idea of a Z-transform. By using Nearest-Neighbor shift, a new signal model can be developed, i.e., Nearest-Neighbor signal model. The main aim is to represent the Nearest-Neighbor signal in timefrequency domain and to analyze the spectrum. For studying the stationary signals, that is their properties are statistically invariant over time, Fourier analysis can be used, but for a non-stationary signal, it requires both time-frequency representation of the signal for complete analysis. In the context of signal analysis, Wigner-Ville distribution can be used effectively to analyze the time-frequency structures of a non-stationary signal. So Wigner-Ville distribution is used to represent the Nearest-Neighbor signal in time-frequency domain. At last, Wigner-Ville distribution of Nearest-Neighbor signal is simulated and absolute and Relative errors of Nearest-Neighbor signal and Wigner-Ville distribution of Nearest- Neighbor signal are calculated.