Quantitative version of a Silverstein's result
classification
🧮 math.PR
keywords
randommatrixprobabilityquantitativesilversteinversioncertaincondition
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We prove a quantitative version of a Silverstein's Theorem on a condition for convergence in probability of the norm of random matrix. More precisely, we show that for a random matrix whose entries are i.i.d. random variables, $w_{i,j}$, satisfying certain natural conditions, is not small with large probability.
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