harmonics expansion $R=\sum a_{l,noise}^m Y_l^m$, coefficients are $a_{l,noise}^m=\sum_{l^{\prime} m^{\prime}} w_{l l^{\prime}}^{m
m^{\prime}}
 n_{l^{\prime}}^{m^{\prime}}$.

Taking into account noncorrelatedness of white noise harmonics a covariation of $a_{l,noise}^m$ may be written as: $$\langle a_{l,noise}^m a_{l^*,noise}^{m^*} \rangle =\sum_{l^{\prime}
m^{\prime}}
 \sum_{l^{\prime\prime} m^{\prime\prime}}
 w_{l l^{\prime}}^{m m^{\prime}}
 w_{l^* l^{\prime \prime}}^{m^* m^{\prime\prime}}
 \langle n_{l^{\prime}}^{m^{\prime}} n_{l^{\prime \prime}}^{m^{\prime
\prime}} \rangle = \\ n^2 \sum_{l^{\prime} m^{\prime}} w_{l
l^{\prime}}^{m m^{ \prime}} w_{l^* l^{\prime}}^{m^* m^{\prime}}$$

And finally noise power spectrum is: $$\langle|a_{l,noise}^m|^2 \rangle =n^2 \sum_{l^{\prime} m^{\prime}}
|w_{l l^{\prime}}^{m
m^ {\prime}}|^2 = n^2 \int d \Omega  w^2(\Omega)|Y_l^m(\Omega)|^2
\label{sp_noise}$$

We use not only unit or zero weights, but unrestricted values. Because of that our equation differs from Peebls’s one in the squared weights.

Then, using maximum likelihood approach to the difference maps we may calculate the amplitude of the spectrum given above.

The power spectrum model make it possible to analyze the noise spectrum measured from the difference maps. The analysis shows that in general the noise spectrum is well described both the model (\[sp\_noise\]) and the white noise model. It is due to a rather perfect COBE coverage of the celestial sphere. But the same analysis shows for the both models the existence of harmonics with an excess power. So in the noise spectrum 