Abstract: Diffusion control in a network of networks (NoN) uses a connection degree of node pairs to control diffusion within the NoN. A method of increasing diffusion includes selecting an unconnected node pair having a lowest connection degree and connected nodes of the selected unconnected node pair. A method of decreasing diffusion includes selecting a connected node pair having a highest connection degree and disconnecting nodes of the selected connected node pair. A network diffusion control system includes the NoN and a diffusion controller to one or both of increase a diffusion rate and decrease the diffusion rate within the NoN. A non-transitory computer readable medium includes instructions that implement the diffusion control within the NoN.

Abstract: A spatio-temporal signal monitoring system includes a sampler configured to receive a radio frequency signal and obtain first compressive sensing measurements of said received signal at a first resolution level, and a signal detector configured to identify at least one signal of interest based on said first compressive sensing measurements and perform second compressive sensing measurements on said at least one signal of interest at a second resolution level, said second resolution level being higher than said first resolution level. The received signal may be analyzed as an array or image having two or more dimensions, based on frequency and on at least one other parameter, such as angle-of arrival, and may be analyzed at a higher level of resolution at the frequencies and angles corresponding to a signal of interest (SOI). Estimates of the frequency and/or the at least one other parameter may be generated by the system.

Abstract: Described is a low power surveillance camera system for intruder detection. The system observes a scene with a known camera motion to generate images with various viewing angles. Next, a background learning mode is employed to generate a low rank matrix for the background in the images. Background null space projections are then learned, which provide a foreground detection kernel. A new scene with known viewing angles is then obtained. Based on the foreground detection kernel and the new input image frame, low power foreground detection is performed to detect foreground potential regions of interest (ROIs), such as intruders. To filter out minimal foreground activity, the system identifies contiguous ROIs to generate the foreground ROI. Focus measures are then employed on the ROIs using foveated compressed sensing to generate foveated measurements. Based on the foveated measurements, the foreground is reconstructed for presentation to a user.

Abstract: A method of and apparatus removing of a plurality of relatively narrow banded signals in a relatively wide banded input signal. The method involves and the apparatus provides for compressively sensing one relatively narrow banded signal in the relatively wide banded input signal and removing one relatively narrow banded signal from the relatively wide banded input signal before detecting and removing another relatively narrow banded signal in the relatively wide banded input signal, the step of and apparatus for compressing sensing occurring with respect to both (i) the input signal with the previously detected narrow banded signals removed therefrom and (ii) a frequency shifted version of (i).

Abstract: Described is a system for foveated compressive sensing. The system is configured to receive an input image f of a scene and initialize a measurement matrix. Global measurements are then performed, with a lower resolution image of the scene thereafter reconstructed. Task salient regions are extracted from the low resolution image. Thereafter, the system estimates a task-specific operator and detects regions-of-interest (ROI) based on the task salient regions. An ROI-adapted and foveated measurement matrix is then generated. Local measurements are then performed on task-relevant ROIs. A higher resolution image can then be reconstructed of the scene to allow for identification of objects in the ROI.

Abstract: Described is a method for accurately reconstructing analog signals. The present invention considers a general parameter estimation problem, extends the utility of compressive sensing to real scenarios, and is able to accurately estimate center frequencies and amplitudes. Specifically, an unknown continuous analog signal comprising a set of arbitrary frequencies and amplitudes is received. A set of non-uniform samples of the unknown continuous analog signal is then obtained at multiple times. Finally, an iterative reconstruction process is utilized to determine a set of frequencies and a set of amplitudes that best fit the set of non-uniform samples in a global minimum problem in order to accurately reconstruct the continuous analog signal.

Abstract: A method and system for processing a sequence of images using fingerprints. A current image in the sequence of images is segmented into a plurality of segments. A plurality of segment fingerprints is created for the plurality of segments. Segments in the plurality of segments are fused together using the plurality of segment fingerprints and a set of prior segment fingerprints created for a previous image in the sequence of images to form a set of master segments.