Abstract: An apparatus and method of analysis for three-dimensional (3D) physical phenomena. The physical phenomena may include any varying 3D phenomena such as time varying polar ice flows. A repesentation of the 3D phenomena is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPC) are selected for Empirical Mode Decomposition into intrinsic modes. The intrinsic modes produced are filtered in order to reconstruct the spatial part of the CPC. Finally, a filtered time series may be reconstructed from the first 3-10 filtered complex principal components.

Abstract: A sensor for monitoring gas content. The sensor comprises a housing defining at least two cavities and a resonating structure positioned in each of the cavities. Each of the resonating structures has a resonant frequency dependent upon a physical characteristic of a gas in its respective cavity. Means for exciting the resonating structures generates output signals therefrom, and means compares the output signals from each of the resonating structures and outputs a comparison signal indicative of a difference between the resonant frequencies of the two structures and the relative gas content of the at least two cavities.

Abstract: An apparatus, article of manufacture, and method of physical phenomena analysis. In particular the physical phenomena may include any varying three-dimensional (3D) physical phenomena such as time varying polar ice flows, for example. A linear trend line and a modeled seasonal cycle may be removed from the representation of the 3D phenomenon to keep subsequent matrix operations within machine capabilities. The representation is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPCs) are selected for Empirical Mode Decomposition (EMD) into intrinsic modes.