Sparse Correlation Kernel Analysis and Reconstruction

This paper presents a new paradigm for signal reconstruction and superresolution, Correlation Kernel Analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class- specific basis functions. The basis functions that we use are the correlation functions of the class of signals we are analyzing. To choose the appropriate features from this large dictionary, we use Support Vector Machine (SVM) regression and compare this to traditional Principal Component Analysis (PCA) for the tasks of signal reconstruction, superresolution, and compression. The testbed we use in this paper is a set of images of pedestrians. This paper also presents results of experiments in which we use a dictionary of multiscale basis functions and then use Basis Pursuit De-Noising to obtain a sparse, multiscale approximation of a signal. The results are analyzed and we conclude that 1) when used with a sparse representation technique, the correlation function is an effective kernel for image reconstruction and superresolution, 2) for image compression, PCA and SVM have different tradeoffs, depending on the particular metric that is used to evaluate the results, 3) in sparse representation techniques, L_1 is not a good proxy for the true measure of sparsity, L_0, and 4) the L_epsilon norm may be a better error metric for image reconstruction and compression than the L_2 norm, though the exact psychophysical metric should take into account high order structure in images.

Preliminary Characterisation of Low-Temperature Bonded Copper Interconnects for 3-D Integrated Circuits

Three dimensional (3-D) integrated circuits can be fabricated by bonding previously processed device layers using metal-metal bonds that also serve as layer-to-layer interconnects. Bonded copper interconnects test structures were created by thermocompression bonding and the bond toughness was measured using the four-point test. The effects of bonding temperature, physical bonding and failure mechanisms were investigated. The surface effects on copper surface due to pre-bond clean (with glacial acetic acid) were also looked into. A maximum average bond toughness of approximately 35 J/m² was obtained bonding temperature 300 C.