Geethu Joseph

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—This work addresses the problem of sequential recovery of temporally correlated sparse vectors with common support from noisy under-determined linear measurements. The Kalman sparse Bayesian learning (SBL) algorithm [1] is an efficient tool for solving the problem when the temporal correlation is modeled using a first order autoregressive model. However,(More)
Since the early 80s, the computer industry has undergone great expansion. Processors are becoming faster and more powerful. Power management issues in computing systems are becoming more and more complex and challenging. An evolution began when the high-performance Pentium processor was driven by a non-standard, less-than-5V power supply, instead of drawing(More)
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