**Tasks to do: **

- Basic Properties of Autocorrelation Function
- Evaluate autocorrelation coefficients of given signal (fcn
*'xcorr'*). - Try options
*'biased, unbiased, coeff, none'*and compare differences in results on following signals:

1. sinusoidal -*s1 - f=15 Hz, fs=200 Hz, A=1, t=1 s*,

2. Gaussian white noise -*b1*- power 0.7, mean value 0,*fs=200 Hz, t=1 s*,

3. Gaussian white noise -*b2*- power 0.7, mean value 0,*fs=200 Hz, t=10 s*,

4. sinusoidal*s1*+ constant component*0.8*,

5. noise b1 + constant component 0.8, - Discuss different properties of given estimations.
- For signals defined in items 1., 2., 3. evaluate biased estimation
of coefficients R[0] and R[12].

ATTENTION !!! To have comparable results, you must set always the seed of random generator of Gaussian noise to 0 by using command "*randn('seed',0);*" !!!

- Evaluate autocorrelation coefficients of given signal (fcn
- Detection of the periodicity in signal using autocorrelation
- Estimate fundamental period of voiced sounds vf5.bin and vm5.bin on the basis of second main maximum of autocorrelation function
- Discuss the problems of this approach.

- Try to estimate the delay between signals from two different input
channles using cross-correlation function.
Sampling frequency of given signals is 8 kHz.

Clean speech signals: s0001-l.bin a s0001-r.bin

Speech with noisy background: x0002-l.bin a x0002-r.bin- a) evaluate cross-correlation from whole signal
- a) evaluate cross-correlation from segmented signal; frame length
*wlen = 256, 512*samples without overlapping.