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<item>
  <id>00815901</id>
  <dt>j</dt>
  <an>00815901</an>
  <augroup>
    <au>Hu, H.</au>
  </augroup>
  <ti>Positive definite constrained least-squares estimation of matrices.</ti>
  <so>Linear Algebra Appl. 229, 167-174 (1995).</so>
  <py>1995</py>
  <pu>Elsevier Science Inc. (North-Holland), New York, NY</pu>
  <lagroup>
    <la>EN</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>least squares estimation</ut>
    <ut>quadratic programming</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.1016/0024-3795(94)00024-8</li>
  </ligroup>
  <abgroup>
    <ab>The problem of finding a symmetric matrix $X$ minimizing $B-XA$ in the least squares sense, under the condition that all eigenvalues of $X$ exceed a given positive value, is solved by means of a sequence of quadratic programming problems. A suboptimal variant, which is guaranteed to converge in a finite number of $QP$ steps, is given as an alternative to the optimal algorithm, which may approach a solution asymptotically.</ab>
    <rv>A.Ruhe (G\"oteborg)</rv>
  </abgroup>
</item>