We consider efficient methods for the recovery of block sparse signals from underdetermined system of linear equations. We show that if the measurement matrix satisfies the block RIP with δ2s 〈 0.4931, then every bl...We consider efficient methods for the recovery of block sparse signals from underdetermined system of linear equations. We show that if the measurement matrix satisfies the block RIP with δ2s 〈 0.4931, then every block s-sparse signal can be recovered through the proposed mixed l2/ll-minimization approach in the noiseless case and is stably recovered in the presence of noise and mismodeling error. This improves the result of Eldar and Mishali （in IEEE Trans. Inform. Theory 55： 5302-5316, 2009）. We also give another sufficient condition on block RIP for such recovery method： 58 〈 0.307.展开更多
The authors investigate the relationship between bias in simulated sea surface temperature （SST） in the equatorial eastern Pacific cold tongue during the boreal spring as simulated by an oceanic general circulation ...The authors investigate the relationship between bias in simulated sea surface temperature （SST） in the equatorial eastern Pacific cold tongue during the boreal spring as simulated by an oceanic general circulation model （OGCM） and minimal wind mixing （MWM） at the surface. The cold bias of simulated SST is the greatest during the boreal spring, at approximately 3℃. A sensi- tivity experiment reducing MWM by one order of magnitude greatly alleviates cold biases, especially in March-April. The decrease in bias is primarily due to weakened vertical mixing, which preserves heat in the uppermost layer and results in warmer simulated SST. The reduction in vertical mixing also leads to a weak westward current in the upper layer, which further contributes to SST warming. These findings imply that there are large uncertainties about simple model parameters such as MWM at the oceanic surface.展开更多
基金Supported by National Natural Science Foundation of China (Grant Nos. 11171299 and 91130009)Natural Science Foundation of Zhejiang Province of China (Grant No. Y6090091)
文摘We consider efficient methods for the recovery of block sparse signals from underdetermined system of linear equations. We show that if the measurement matrix satisfies the block RIP with δ2s 〈 0.4931, then every block s-sparse signal can be recovered through the proposed mixed l2/ll-minimization approach in the noiseless case and is stably recovered in the presence of noise and mismodeling error. This improves the result of Eldar and Mishali （in IEEE Trans. Inform. Theory 55： 5302-5316, 2009）. We also give another sufficient condition on block RIP for such recovery method： 58 〈 0.307.
基金supported by the National Basic Research Program of China (Grant Nos. 2010CB950502, 2010CB951904,and 2010AA012303)LASG Free Exploration Fundthe National Natural Science Foundation of China (Grant Nos. 40906012 and 40775054)
文摘The authors investigate the relationship between bias in simulated sea surface temperature （SST） in the equatorial eastern Pacific cold tongue during the boreal spring as simulated by an oceanic general circulation model （OGCM） and minimal wind mixing （MWM） at the surface. The cold bias of simulated SST is the greatest during the boreal spring, at approximately 3℃. A sensi- tivity experiment reducing MWM by one order of magnitude greatly alleviates cold biases, especially in March-April. The decrease in bias is primarily due to weakened vertical mixing, which preserves heat in the uppermost layer and results in warmer simulated SST. The reduction in vertical mixing also leads to a weak westward current in the upper layer, which further contributes to SST warming. These findings imply that there are large uncertainties about simple model parameters such as MWM at the oceanic surface.
