Performing Raw Data Fitting

When performing raw data fitting, various analytical tools can be employed to explore data characteristics. For instance, conducting MATLAB analysis in the time domain allows for temporal decomposition of signals, providing deeper insights into frequency and amplitude properties. This can be implemented using functions like plot() for visualization and findpeaks() for amplitude characterization. Additionally, frequency domain analysis can be performed by applying Fourier transforms through MATLAB's fft() function to convert signals into frequency domain representations, enabling better understanding of spectral characteristics. The transformation process typically involves windowing techniques and zero-padding for spectral resolution optimization. Furthermore, wavelet analysis using functions like cwt() (Continuous Wavelet Transform) or dwt() (Discrete Wavelet Transform) facilitates time-frequency analysis, allowing comprehensive investigation of signal properties across both temporal and spectral dimensions through multi-resolution analysis.