In this paper, a novel and simple one-port de-embedding technique has been applied to through-silicon-via (TSV) characterization and modeling. This method utilized pad, via, and line structures to extract the equivalent circuit model of TSV. The main advantage of this de-embedding method is that it can reduce the chip area to fabricate test element groups (TEGs) for measurements while keeping S-parameter measurement accuracies. We also analyzed the electrical characteristics of substrate coupling and TSV equivalent impedance. Our results shows good agreements between measurement data and the equivalent circuit model up to 20GHz.

A method of motion segmentation in RGB image sequences is presented in details. The method is based on moving object modeling by a six-variate Gaussian distribution and a hidden Markov random field (MRF) framework. It is an extended and improved version of our previous work. Based on mathematical principles the energy expression of MRF is modified. Moreover, an initialization procedure for the first frame of the sequence is introduced. Both modifications result in new interesting features. The first involves a rather simple parameter estimation which has to be performed before the use of the method. Now, the values of Maximum Likelihood (ML) estimators of the parameters can be used without any user's modifications. The last allows one to avoid finding manually the localization mask of moving object in the first frame. Experimental results showing the usefulness of the method are also included.