**Tasks to do: **

- Compare short-time spectrum estimation using DFT and LPC analysis
- For the evaluation of algorithm use voiced part of speech vm0.bin.
- AR cofficients of the signal could be computed using fcn
*lpc*. Parameters of AR model will be*p=16, N = 512* - LPC spectrum is given as frequency response synthesizing filter
( fcn
*freqz*) - Draw both short-time spectrum estimations (DFT and LPC) into one plot for comparison !!
- Observe influence of wieghting of analyzed signal by Hamming window.
- Observe influence of LPC spectrum on amplification parameter
*G*. - Compare
*G*or*E_p*respectively evaluated as:- output of fcn
*lpc*, - by the formula from AR and autocorrelation coefficients,
- by the direct evaluation of power of error signal.

- output of fcn
- Observe the results for different order of AR model
*p=16, 10, 6*. Explain the results !!

- For the evaluation of algorithm use voiced part of speech vm0.bin.
__Example:__Compare possible spectral resolution in spectral analysis using DFT aan LPC.- Choose optimal order of AR model for particular task specified bellow.
- Evaluate spectral estimation from follwoing number of samples:
*N=64*and*N= 256*. - Use weigthing of the signal by Hamming window.
- sinusoidal:
*f=13 Hz*,*fs= 100 Hz* - 2 sinusoidals of close frequencies:
*f1=13 Hz*,*f2=15 Hz*,*fs= 100 Hz*