HardySpicer schrieb:
> On Jan 29, 6:35 am, Sebastian Doht<seb_d...@lycos.com>  wrote:
>> rit schrieb:
>> what is relation between noise variance and power spectral density?
>>
>>
>>
>>> Thanks
>>
>> Parseval's theorem
>
> Same as the area under the spectral density curve.

Of course but when I was a student I could better understand things 
which I could mathematically derive myself. So Parseval's theorem tells 
why one should compute the area under the graph. Of course this assumes 
the opener really wants to understand rather than looking for cheap and 
easy answers.

On Jan 29, 6:35&#4294967295;am, Sebastian Doht <seb_d...@lycos.com> wrote:
> rit schrieb:
> what is relation between noise variance and power spectral density?
>
>
>
> > Thanks
>
> Parseval's theorem

Same as the area under the spectral density curve.

rit schrieb:
what is relation between noise variance and power spectral density?
>
> Thanks
>
>

Parseval's theorem

On Jan 28, 9:29&#4294967295;pm, rit <u...@compgroups.net/> wrote:
> can anyone tell me how to calculate noise variance (sigma^2/2),if noise power spectral density is -162dBm/hz. Noise is additive white circularly symmetric gaussian complex noise. what is relation between noise variance and power spectral density?
>
> Thanks

The area under the graph.

>can anyone tell me how to calculate noise variance (sigma^2/2),if noise
power spectral density is -162dBm/hz. Noise is additive white circularly
symmetric gaussian complex noise. what is relation between noise variance
and power spectral density?
>
>Thanks
>
>
>

hint: what is the relation between noise variance and noise power?
(assuming the process is ergodic)

can anyone tell me how to calculate noise variance (sigma^2/2),if noise power spectral density is -162dBm/hz. Noise is additive white circularly symmetric gaussian complex noise. what is relation between noise variance and power spectral density?

Thanks