&&\frac{\partial c}{\partial\mu^i}  =0\mbox{\ \ \ }\nonumber\\
&\Rightarrow& 
\left\langle\check A {\bf h}(\check\mu^j) + {\bf n}, \frac{\partial
{\bf h}}{\partial\mu^i}\right\rangle = 0\nonumber\\
&\Rightarrow&  \left\langle{\bf h}(\check\mu^j), \frac{\partial
{\bf h}}{\partial\mu^i}\right\rangle = -\frac{1}{\check
A}\left\langle{\bf n}, \frac{\partial
{\bf h}}{\partial\mu^i}\right\rangle.\end{aligned}$$

In the limit of high SNR the mean square errors in the measurement of the parameters are characterised by the so called covariance matrix $C^{ab}$ [@HEL] defined as, $$\begin{aligned}
\label{cov}
\Gamma_{ab} &=& \left\langle\frac{\partial{\bf s}}{\partial \mu^a}(\bbox{\mu}),
 \frac{\partial 
{\bf s}}{\partial \mu^b}(\bbox{\mu})\right\rangle\\
C^{ab} &=& \left[\Gamma^{-1}\right]^{ab}\end{aligned}$$

From the expression for the Fourier transform in the stationary phase approximation (eqn. (\[FT\])) and from the definition of the scalar product (eqn. (\[scal\])) we see that the phase function in the Fourier transform simply cancel out and only the amplitude remains. We also find that $C^{ab} \propto \check A^{-2}$.

The idea now is to compare the results of the Monte Carlo simulations with those obtained via eqn. (\[cov\]). In the limit of high SNR, it is expected that the errors will agree with those obtained from the covariance matrix. In the following sections we briefly mention the results of the Monte Carlo simulations and then analyse in detail eqn. (\[m1\]). The goal is to first check the agreement between the two and then understand how 