INSTANTANEOUS FREQUENCY ESTIMATION Includes different methods to estimate the instantaneous frequency for given time-domain signal These different techniques include: (i) Finite Phase Difference (ii) Weighted Phase Difference (iii) Zero-Crossing (iv) Adaptive Estimators (v) Least Squares (vi) Peak of Spectrogram (vii) Peak of Wigner-Ville Distribution (viii) Peak of Polynomial Wigner-Ville Distribution PARAMETERS: SIGNAL One dimensional input signal. ESTIMATED FREQUENCY ARRAY One dimensional output signal containing the estimated instantaneous frequency (IF) law for given input signal. EXPLANATION OF VARIOUS TECHNIQUES: (i) Finite Phase Difference Estimates the IF law of the input signal using the general phase difference method. Only first, second, fourth and sixth order phase difference estimators are available in the case when no smoothing is required. The signal phase is unwrapped when a fourth or a sixth order estimator is applied (ii) Weighted Phase Difference This function uses the Kay weighted difference estimator. A sliding Kay window is used to smooth the phase. The local smoothed estimate inside the moving quadratic window is computed each time the window moves. (iii) Zero Crossings Estimates the IF law of the input signal using the zero-crossing estimation algorithm. It estimates the frequency by taking the average number of zero-crossings within a sliding window. (iv) Adaptive Estimators Two methods can be selected here, the least mean square (LMS) adaptive IF estimator and the recursive least square (RLS) adaptive IF estimator. The LMS method is based on a single tap linear prediction filter which has its coefficients updated as each new data sample is received. The positive adaptation constant controls the rate adaptation. The RLS method is based on a single tap linear prediction filter which has its coefficients updated as each new data sample is received. The forgetting factor controls the rate of adaptation. Both the adaptation constants must be positive. (v) Least Squares Estimates the IF law of the input signal by obtaining the phase of the input signal and then fitting a polynomial. The order of the polynomial is selected using the parameter order. The order of the polynomial to be fitted to the can be specified. (vi) Peak of Spectrogram Estimates the IF law of the input signal using the peak of the spectrogram method. SEE ALSO: spec (vii) Peak of Wigner-Ville Distribution Estimates the IF law of the input signal using the peak of the Wigner-Ville distribution method. SEE ALSO: wvd (viii) Peak of Polynomial Wigner-Ville Distribution Peak of the sixth order polynomial Wigner-Ville distribution IF estimation algorithm. SEE ALSO: pwvd6