Least-squares error functions are widely used in the determination of the parameters of models of a system. When this procedure is iterative, the problem of deciding when to stop iterating arises. Usually a threshold is defined, so that when the error function falls below this value, the least-squares error procedure can be stopped and the solution is found. However, this threshold depends on the uncertainty of the measurements. In this paper, the cost function PDF (probability density function) is analyzed to obtain a closed-form expression for the estimation of this threshold, in the framework of impedance spectroscopy.

Eddy current testing (ECT) is a non destructive technique that can be used in the measurement of conductive material thickness. In this work a machine learning algorithm (support vector machine - SVM) is applied to ECT data, obtained for three different types of conductive plates, and classifies their thicknesses. Eddy currents are induced by imposing a voltage step in an excitation coil, while a giant magnetoresistor (GMR) magnetic sensor measures the transitory magnetic field intensity in the sample vicinity. An experimental validation procedure, including machine training with linear and exponential kernels and classification errors, was made for each metal type with sets of sample thicknesses up to 7.5 mm.

Cloud monitoring and prediction is crucial to air traffic and weather forecast. Clouds play a key role in solar radiation balance. These issues have prompted Sieltec Canarias S.L. and AEMET to develop an automatic system of cloud observation (SONA). This system provides cloud cover percentage using all-sky images, which are processed by neural networks. Once the system has detected and recorded cloud images, a cloud motion technique makes possible to obtain “velocity fields”, corresponding to different layers of clouds. The evolution in time of these velocity fields is a powerful tool to provide very short term forecasting (less than 1 hour) of cloudiness (known as cloud nowcasting). In the future, this information, combined with Radiative Transfer Models, may be used for solar radiation nowcasting (Global Horizontal Irradiance –GHI- and Direct Normal Irradiance –DNI-)

The combination of systems exploiting binary-divided and pulse-driven Josephson arrays allows the generation of sinewaves with amplitudes of up to 10 V and very low harmonic distortion (-122 dBc). We present results from the combination of a 1 V binary divided Josephson array employed as a multilevel digital to analogue converter and a pulse driven array that is programmed to cancel the harmonic content present in the stepwise approximated output of the binary array. The synthesized waveform can be locked to a timing reference for ultimate frequency stability. The quantum nature of the Josephson synthesizers guarantees the stability of the amplitude. The unprecedented amplitudes available with this spectral purity open new possibilities for testing of electronic modules and analogue to digital converters.

This paper presents a new and accurate experimental method based on electrical harmonic distortion analysis to determine mechanical characteristics (resonant frequency) of MEMS devices used in widespread applications as in energy scavenging, cantilever-based microsystems for gas sensing and atomic force microscopy or in any kind of MEMS resonators. Resonant frequencies ranging from 0.8 kHz to 5 kHz of electrostatic actuated MEMS-based harvesters have been measured by this technique with an uncertainty as low as a few parts in 10³ constituting an outstanding result compared to the other methods.