Signal analysis algorithms for frequency-domain decomposition and spectral estimation.
| Algorithm | Description |
|---|---|
| Fast Fourier Transform | Efficient computation of the Discrete Fourier Transform using the Cooley-Tukey radix-2 algorithm |
| Real-Input FFT | Length-N real FFT via even/odd split into two N/2-point complex DFTs, halving compute and memory |
| Power Spectral Density | Estimation of signal power distribution across frequencies using Welch's method |
| Discrete Cosine Transform | Real-valued frequency decomposition via cosine basis functions, computed through FFT |
| Signal Detectors | Peak hold, zero-crossing counter, and RMS envelope detectors for real-time signal monitoring |
| Decibels | ToDecibels / FromDecibels conversion helpers with zero-floor guard, plus attenuation and ripple utilities |
| Goertzel Algorithm | Single-bin DFT via a second-order recurrence for O(N) tone detection with O(1) memory |
| Discrete Wavelet Transform | Multilevel Haar / Daubechies filter bank for O(N) time-frequency decomposition with perfect reconstruction |
| Hilbert Transform | Analytic signal and instantaneous amplitude/phase/frequency via FFT one-sided spectrum or FIR approximation |
| Mel Filterbank / MFCC | Sparse triangular mel filterbank (HTK/Slaney scale and normalisation), log-mel and orthonormal DCT-II cepstrum |
| Sub-domain | Description |
|---|---|
| Windowing | Window functions (Rectangular, Hamming, Hanning, Blackman) for FFT preprocessing |
Note: For control system analysis tools (Frequency Response, Root Locus), see Control Analysis.