Parameterizing neural power spectra into periodic & aperiodic components.

Compares FBMC to OFDM based schemes. Reproduces all figures from “Filter bank multicarrier modulation schemes for future mobile communications”, IEEE Journal on Selected Areas in Communications, 2017.

Allows to reproduce all figures from "Pruned DFT Spread FBMC: Low PAPR, Low Latency, High Spectral Efficiency", IEEE Transactions on Communications, 2018

Simulates pruned DFT spread FBMC and compares the performance to OFDM, SC-FDMA and conventional FBMC. The included classes (QAM, DoublySelectiveChannel, OFDM, FBMC) can be reused in other projects.

Spectrum Analyzer with Arduino: An Arduino Due and a PC give you the frequency response of any device, filter or amplifier, up to 100kHz.

Functions for creating speech features in MATLAB.

Senior Design Project at UH

Least-squares (sparse) spectral estimation and (sparse) LPV spectral decomposition.

Adaptive, sine-multitaper power spectral density estimation in R

Ground acceleration records are simulated using the non-stationnary Kanai–Tajimi model

a package for spectral parametrization in python based on the IRASA algorithm

Calculation of PSD of seismic waves in order to measure the impact of culture noise during the COVID-19 pandemic.

This web app allows you to decompose your signal data or time series using FFT and gives the opportunity to interactively investigate the signal and its spectrum (frequency spectrum, power spectrum, periodogram, and its power spectral density) using the advantage of Plotly package.

Scripts to determine the power spectral density (PSD) of blazar light curves in python2

Decipher and classify accelerometer and gyroscope signal patterns of different activities collected from smartphone sensors.

das stream utilities and catalog client in C

Statistical Digital Signal Processing and Modeling

Minimalist Matlab implementation of a random process generation in one point

Modelling and simulation of major components in a digital communication system