matlab上机作业(数字信号处理)Computation Exercises:1.Generate a stationary process AR(2) denoted by .Suppose that Here,the parameters of are determined by yourselves.Then generate a white noise with the variance .The received signal iswi
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matlab上机作业(数字信号处理)Computation Exercises:1.Generate a stationary process AR(2) denoted by .Suppose that Here,the parameters of are determined by yourselves.Then generate a white noise with the variance .The received signal iswi
matlab上机作业(数字信号处理)
Computation Exercises:
1.Generate a stationary process AR(2) denoted by .Suppose that
Here,the parameters of are determined by yourselves.Then generate a white noise with the variance .The received signal is
with a variable SNR.Put the received the signal to a Wiener-filter,the length of the filter is N.And the output is denoted by .
① Study on the relationship between the cost function and SNR of the signal,provided the length of the Wiener-filter is given.
② Study on the relationship between the cost function and length of the filter,provided the SNR is given.
③.When one-step prediction is done,how about the cost function varies with the SNR and length of the Wiener-filter.
matlab上机作业(数字信号处理)Computation Exercises:1.Generate a stationary process AR(2) denoted by .Suppose that Here,the parameters of are determined by yourselves.Then generate a white noise with the variance .The received signal iswi
Computation Exercises:
1.Generate a stationary process AR(2) denoted by .Suppose that
Here,the parameters of are determined by yourselves.Then generate a white noise with the variance .The received signal is
with a variable SNR.Put the received the signal to a Wiener-filter,the length of the filter is N.And the output is denoted by .
① Study on the relationship between the cost function and SNR of the signal,provided the length of the Wiener-filter is given.
② Study on the relationship between the cost function and length of the filter,provided the SNR is given.
③.When one-step prediction is done,how about the cost function varies with the SNR and length of the Wiener-filter.