J. Briaire

UNCERTAINTY IN GAUSSIAN NOISE GENERALIZED FOR CROSS-CORRELATION SPECTRA

The ensemble average and variance of Gaussian noise measured as cross-correlation spectra are calculated as a function of the number of time averages. The calculations are based on the Carson–Campbell theorem which treats noise spectra as a collection of individual deterministic pulses transformed into the frequency domain. We have compared our calculations with experimental results on metal film resistors. There is an excellent agreement between the predicted and the measured statistical behavior.

1/f Noise in magnetic Ni80Fe20 single layers and Ni80Fe20/Cu multilayers

We have investigated the room temperature 1/f noise of microstructured soft magnetic Ni80Fe20 films, showing the anisotropic magnetoresistance effect, and of Ni80Fe20/Cu magnetic multilayers, showing the giant magnetoresistance effect. We find that the 1/f noise in magnetic multilayers is considerably enhanced with respect to the noise of the single domain layer and attribute this to the complex domain structure of the multilayer.

1/f noise in magnetic Ni80Fe20 single layers and Ni80Fe20/Cu multilayers

We have investigated the room temperature 1/f noise of microstructured soft magnetic Ni80Fe20 films, showing the anisotropic magnetoresistance effect, and of Ni80Fe20/Cu magnetic multilayers, showing the giant magnetoresistance effect. We find that the 1/f noise in magnetic multilayers is considerably enhanced with respect to the noise of the single domain layer, which sets a limit on the usability of giant magnetoresistance materials for low‐frequency applications.

The influence of a digital spectrum analyzer on the uncertainty in 1/f noise parameters

When noise is used as a diagnostic tool to determine the reliability of a device, not only the noise parameters itself, but also the uncertainty in these noise parameters are important. For good devices, this uncertainty will be Gaussian. However, because of non-linear measurement errors caused by a digital spectrum analyzer, this uncertainty might deviate from Gaussianity. We have estimated this additional error through simulations. We conclude that this error can often be ignored.