This paper addresses the generation of spectrally pure sinewaves by combining the feedback structure of a ΣΔ loop with digital cancellation of unwanted spectral components in the output signal. In particular, the non-linearities of the in-loop Digital to Analog Converter (DAC) are compensated by applying a digital pre-distortion to the DAC input, and the feedback architecture is used to enhance the performance of the all digital estimation and cancellation algorithm.

In the paper a new method of fault detection and location of a single soft fault in analog parts of mixed signal microsystems based on microcontrollers is presented. The idea of the method bases on the transformation which maps changes of the time response of the tested circuit on a square impulse resulting from changes of values of respective elements onto identification curves on a plane. The method consists of two stages. In the first stage a fault dictionary of an analog part in the form of a family of identification curves is generated and it is placed in the program memory of the microcontroller. In the second stage detection and a location of the fault are carried out.. This method does not require extra hardware in the microsystem. The measuring-diagnosis procedure is realised only by the microcontroller already existing in the microsystem.

This paper describes a system to remotely monitor and control complex stand-alone photovoltaic plants. In normal conditions the developed system registers and reports the overall performances; in case of incorrect behaviors it seasonably informs the operators. Moreover through appropriate instructions sent by users it allows to change the configurations of the plant and the settings of the measurement system as well. Several means of communications are available due to the need to adapt the system to the different operative conditions. However for a more general and flexible implementation, the remote control is carried out through the GSM network and in special way exploiting the SMS (Short Message Service) feature.

In this paper we describe the design of digital architectures suitable for the implementation of measurement data classification based on Support Vector Machines (SVMs). The performance of such architectures are then analyzed. The proposed approach can be applied for solving identification and inverse modelling problems, and for processing complex measurement data. Two very different case studies where real-time processing is of paramount importance are discussed: a nonlinear channel equalization and a high energy physics classification task.

Measuring procedures in some cases require connection of two measuring objects or parts of equipment which terminals should not have common potential. Achievement of these requirements is inappropriate by using the transformer coupling because of its non-linear transfer function. Optical transfer of digital signals by using optocoupler provides the precision and stability needed to accurately signal monitoring.