The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400—407]. After five decades of continual development, it has developed into an important area ...
The problem of estimating a linear transformation between two finite dimensional vector spaces is considered, when the observed vectors in both spaces are subject to error, and there is an ...
Information theory provides the fundamental framework for understanding and designing data compression algorithms. At its core lies the concept of entropy, a quantitative measure that reflects the ...
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