SpectrumSolvers6.20

Electrical or information theory engineers are well aware that the spectral analysis of deterministic signals was introduced as a means to characterize signals in the frequency domain. Periodic signals are analyzed in the frequency domain using Fourier series, and the finite aperiodic energy signals using Fourier transform. The Fourier transform of the autocorrelation function represents the power spectral density (PSD) of the signal that connects time and frequency domains.Knowing how the strength of a signal is distributed in the frequency and time domain is a central point in designing any linear time-invariant (LTI) filter used in many currently used MIMO (multi-input multi-output) systems.

Calculate PSD plots by choosing an estimation method

SpectrumSolvers is a handy software tool designed specifically for engineers, scientists, spectrum specialists or junior researchers.The program focuses on calculating the power spectral density based on Steve Kay's book about modern spectral estimation in statistical signal processing.With this program you can choose from several estimation methods. Because PSD results for each estimation method can differ drastically from one another, it is recommended that you try several ones before you select the estimation that better represents your PSD diagram. Furthermore, if you vary input parameters or entry number of points, you may notice some discrepancies that surely affect how PSD is calculated and displayed.When choosing the input parameters, you also have the possibility to change array sizes and see how zero padding affects your results.A few estimation methods included in the application are Recursive Maximum Likelihood Estimation, Autocorrelation, Burg, Durbin, Lockheed, Mayne-Firoozan, Covariance, Periodogram, Blackman-Turkey, Akaike and Modified Yule-Walker Equations.

Efficient signal analyzer

All in all, SpectrumSolvers is a handy utility for those who work with spectral analyzers or do research in the filed of information theory and signal processing. But it can also be a starting point for students and aspiring scientists, since understanding the program requires extensive information theory knowledge.