A combined theory of the micromagnetic and Monte Carlo simulations is established to analyze the thermal property of a nano-sized magnetic grain. The Langevin equation of a grain's magnetic moment is the Landau-Lifshitz equation augmented by a "random-field" term representing the thermal-agitated force. The angular distribution of the magnetic moment of the grain is studied via its time evolution process. The switching of the magnetic moment vector between two energy-minimum states is observed. A simple analytical expression is obtained for the simulated attempt frequency f0, which is related to the magnetic constant of the nano-grain, and agrees well with the phenomenological value.

Regular on-site testing is an elementary means to obtain real-time data and state of Electromagnetic Compatibility (EMC) of electronics systems. Nowadays, there is a lot of measured EMC data while the application of the data is insufficient. So we put forward the concept of EMC model synthesis. To carry out EMC data mining with measured electromagnetic data, we can build or modify models and synthesize variation rules of electromagnetic parameters of equipment and EMC performance of systems and platforms, then realize the information synthesis and state prediction. The concept of EMC reliability is brought forward together with the definition and description of parameters such as invalidation rate and EMC lifetime. We studied the application of statistical algorithms and Artificial Neural Network (ANN) in model synthesis. Operating flows and simulation results as well as measured data are presented. Relative research can support special measurement, active management and predictive maintenance and replenishment in the area of EMC.