Existing compressed sensing algorithms fail when applied to radar target detection in the presence of a large gap frequency band, i.e., signals separate, discontinuous bands. A new algorithm based on subdivision-fusion scheme is proposed solve this problem. The main goal use structured matrix an advantage and obtain good range resolution spite high coherence. Parameters influencing performance ...

Performance and availability are two critical requirements of today’s systems. Current dynamic AOP approaches have addressed the performance issue from one specific dimension: the performance of code after the weaving process. Other performance factors may have a great impact on overall system performance. This includes performance of the weaving process itself and also system availability in s...

We extend ideas from compressive sensing to a structured sparsity model related to fusion frames. We present theoretical results concerning the recovery of sparse signals in a fusion frame from undersampled measurements. We provide both nonuniform and uniform recovery guarantees. The novelty of our work is to exploit an incoherence property of the fusion frame which allows us to reduce the numb...

Transmitted data may be corrupted by both noise and data loss. Grassmannian frames are in some sense optimal representations of data transmitted over a noisy channel that may lose some of the transmitted coefficients. Fusion frame (or frame of subspaces) theory is a new area that has potential to be applied to problems in such fields as distributed sensing and parallel processing. Grassmannian ...

Among the hand woven sarees of India, Paithani is famous and has played a significant role in weaving together the socio-cultural fabric of Maharashtra since it is traditionally a part of the trousseau of every Maharashtra bride. The aim of the study was to document the existing weaving traditions of Paithani and explore the possibility of weaving Paithani as a yardage with different product la...

This paper studies the design of data fusion algorithm for asynchronous system with integer times sampling. Firstly, the multisensor asynchronous samplings is mapped to the basic axis, accordingly a sampling sequence of single sensor can be taken. Secondly, aiming at the sensor with the densest sampling points, the modified parallel filtering is given. Afterwards, the sequential filtering fusio...

Fusion frames consist of a sequence of subspaces from a Hilbert space and corresponding positive weights so that the sum of weighted orthogonal projections onto these subspaces is an invertible operator on the space. Given a spectrum for a desired fusion frame operator and dimensions for subspaces, one existing method for creating unitweight fusion frames with these properties is the flexible a...

Fusion frames are collection of subspaces which provide a redundant representation of signal spaces. They generalize classical frames by replacing frame vectors with frame subspaces. This paper considers the sparse recovery of a signal from a fusion frame. We use a block sparsity model for fusion frames and then show that sparse signals under this model can be compressively sampled and reconstr...