The presence of electrical noise is a common source of uncertainty, especially in the case of high bandwidth and low signal amplitude level. The development of high performance nanoelectronic integrated circuits and systems with increased functionality, high bandwidth and low signal power levels requires EMI-aware design. Such a design has to be based on accurate signal- and noise modeling to minimize the uncertainty in the operation of the circuits and systems. In this contribution we present advances in measurement and modeling of noisy electromagnetic fields using two-probe scanning and correlation analysis. Stochastic electromagnetic fields with Gaussian amplitude probability distribution can be fully described by auto- and cross correlation spectra of the field components. In case of digital circuitry clocked by a single clock pulse, the generated EMI is a cyclostationary process where the expectation values of the EMI are periodically time dependent according to the clock frequency and which have to be considered in modeling the EMI. Correlation analysis provides a basis for accurate modeling of noisy electromagnetic fields and, for strategies in computer aided design to reduce EMI. The determination of the near-field correlation spectra of the EMI radiated from devices and circuits by two-point measurements as well as methods to compute from these data the EMI distribution in complex environments are described. The amount of data required for the characterization of stochastic EM near fields can be reduced considerably by principal component analysis. The influence of noise on signal uncertainty is discussed.     «

The presence of electrical noise is a common source of uncertainty, especially in the case of high bandwidth and low signal amplitude level. The development of high performance nanoelectronic integrated circuits and systems with increased functionality, high bandwidth and low signal power levels requires EMI-aware design. Such a design has to be based on accurate signal- and noise modeling to minimize the uncertainty in the operation of the circuits and systems. In this contribution we present a...     »