This paper proposes a new design check system that works in three steps. First, hotspots such as pinching/bridging are recognized in a product layout based on thorough process simulations. Small layout snippets centered on hotspots are clipped from the layout and similarities between these snippets are calculated by computing their overlapping areas. This is accomplished using an efficient, rectangle-based algorithm. The snippet overlapping areas can be weighted by a function derived from the optical parameters of the lithography process. Second, these hotspots are clustered using a hierarchical clustering algorithm. Finally, each cluster is analyzed in order to identify the common cause of failure for all the hotspots in that cluster, and its representative pattern is fed to a pattern-matching tool for detecting similar hotspots in new design layouts. Thus, the long list of hotspots is reduced to a small number of meaningful clusters and a library of characterized hotspot types is produced. This could lead to automated hotspot corrections that exploit the similarities of hotspots occupying the same cluster. Such an application will be the subject of a future publication.

No abstract

Local active noise control systems generate a zone of quiet at the physical error sensor using one or more secondary sources to cancel acoustic pressure and its spatial derivatives at the sensor location. The resulting zone of quiet is generally limited in size and as such, placement of the error sensor at the location of desired attenuation is required, which is often inconvenient. Virtual acoustic sensors overcome this by projecting the zone of quiet away from the physical sensor to a remote location. The work described here investigates the effectiveness of using virtual sensors in a pure tone diffuse sound field. Stochastically optimal virtual microphones and virtual energy density sensors are developed for use in diffuse sound fields. Analytical expressions for the controlled sound field generated with a number of control strategies are presented. These expressions allow the optimal control performance to be predicted. Results of numerical simulations and experimental measurements made in a reverberation chamber are also presented and compared.

This paper builds on earlier work by the same authors to derive expressions for the time-averaged acoustic energy density in the frequency domain using the auto- and cross-spectral densities of multiple microphone elements. Expressions for the most common three-dimensional geometric arrangements are derived. Simplified expressions for use with two channel spectrum analysers are also presented.

Acoustic energy density has been shown to exhibit lower spatial variance in reactive sound fields compared to the acoustic potential energy estimate offered by microphones, making it a very useful measure of the acoustic energy within an enclosure. Previously, frequency domain time-averaged energy density estimates have come about by estimating the pressure average and particle velocity between two closely spaced microphones using either analog or digital electronics. A frequency domain expression can be obtained by adding the weighted sum of the auto-spectral densities of both the pressure and particle velocity magnitude. The purpose of this letter is to derive an expression for the time-averaged acoustic energy density in the frequency domain using the autoand cross-spectral densities between the two closely spaced microphones. The resulting expression is validated numerically.