Tiken wrote:
> HI, I am currently doing a project on estimation of power spectral
> density using DSP processort(Blackfin).I am bit confused abt how to
> approach initially for the same.I am thinking to implement  algorithms
> based on parametric estimation. What could be the best and convinient
> type of the signal to be used for the same(Test vectors are to be used
> actually) and how to generate such test vectors?
> 

You could start with test vectors that match your parametric estimation 
scheme.

For example, a simple spectral estimator (I forget the name) can be 
obtained as follows. For a given order of predictor, find the optimum 
linear predictor, h, for the signal of interest. An estimate of the 
spectrum is given by S(w) = 1/(H(w)H*(w)), where is H is the DFT of h.

In this case, generate test vectors which are the output of analysis 
filter 1/h driven by white noise. This will provide the best case 
scenario in which your estimator will work.

Sorry, but I don't have any references in front of me to provide more 
details of other estimators.

Greg

HI, I am currently doing a project on estimation of power spectral
density using DSP processort(Blackfin).I am bit confused abt how to
approach initially for the same.I am thinking to implement  algorithms
based on parametric estimation. What could be the best and convinient
type of the signal to be used for the same(Test vectors are to be used
actually) and how to generate such test vectors?