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1、1Computer Experiments on adaptive equalizationRandom-number generator 1 provides the test signal , used for probing the channel, whereas random-number generator 2 serves as the source of additive white noise that corrupts the channel output. These two random-number generators are independent of each

2、 other. The adaptive equalizer has the task of correcting for the distortion produced by the channel in the presence of the additive white noise. Random-number generator 1, after suitable delay, also supplies the desired response applied to the adaptive equalizer in the form of a training sequence.

3、nxnv23The random sequence applied to the channel input consists of a Bernoulli sequence, with and the random variable having zero mean and unit variance. The impulse response of the channel is described by the raised cosine nx1nxnxotherwisennwhn3 , 2 , 10)2(2cos(121where the parameter w controls the

4、 amount of amplitude distortion produced by the channel, with the distortion increasing with w. The eigenvalue spread of the correlationmatrix of the tap inputs also increases with w.nvzero mean, and 001. 02vGaussian white noise. 4The equalizer has M = 11 taps.1z1z1z1z)(nu0w1w2w3w10w)(ny)(ndn5Experi

5、ment 1 Effect of Eigenvalue Spread075. 05 . 3 , 3 . 3 , 1 . 3 , 9 . 2wLMS algorithmYou should carry out over 500 independent trials of the experiment, and plot the ensemble average of squared- error versus n, and the ensemble average impulseresponse of the adaptive equalizer after 1000 iterations. )

6、(2ne6Experiment 2 Effect of Step-Size parameter075. 0 ,025. 0 ,0075. 0Repeat experiment 1.Experiment 3 Using RLS algorithm and repeat experiment 1.LMS algorithm004. 01Experiment 4 Performance comparison of LMS and RLSLMS algorithm075. 01 . 3wRLS algorithm004. 011 . 02v1 . 02vPlease make comments on all these

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