Researching with the Signals & Systems Lab
This tool provides an integrated environment for a wide range of tasks involving the analysis of signals and systems in research. In particular, it supports signal processing, system simulation, design and analysis of control systems, adaptive filtering, non-stationary signal analysis, and statistics. Furthermore, the lab is used for:
Time-frequency Domain (TFD) and autoregressive (AR) modeling of a human EEG signal.
- Data preprocessing—Such as for digital-filter design, windowing, resampling/interpolation, and detrending/prefiltering
- Frequency analysis—Based on a discrete-time Fourier transform
- Control-system analysis—Including computation of impulse and step responses
- Analysis of stochastic processes—Using spectral analysis, covariance-function estimation, and probability distribution function (PDF) fitting
- Adaptive filtering—Including recursive estimation of time-varying models
- Statistical analysis—For estimating parametric distributions from data as well as computing error functions and their inverses for hypothesis testing and finding confidence intervals
- Accurate uncertainty descriptions—the Lab supports embedded Monte Carlo simulations for descriptions of uncertainty, visualized as scatter plots or semi-transparent confidence bands