Discrete norm approximation of the $L^p$ norm for spline functions











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In Theorem 5.2 in Lynche (1988) "A data reduction strategy for splines with applications to the approximation of functions and data", a bound for the difference between the $(l_2,t)$ and $L^2$ norms is given (Equation 5.8), where $(l_2,t)$ is the discrete weighted norm defined in Equation 5.4.



Could this result be extended to the general $(l_p,t)$ and $L^p$ $(l_2,t)$ norms
for $1leq pleqinfty$? Or at least for $p=1$?



Thanks in advance.










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    In Theorem 5.2 in Lynche (1988) "A data reduction strategy for splines with applications to the approximation of functions and data", a bound for the difference between the $(l_2,t)$ and $L^2$ norms is given (Equation 5.8), where $(l_2,t)$ is the discrete weighted norm defined in Equation 5.4.



    Could this result be extended to the general $(l_p,t)$ and $L^p$ $(l_2,t)$ norms
    for $1leq pleqinfty$? Or at least for $p=1$?



    Thanks in advance.










    share|cite|improve this question









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    Fabio.100 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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      up vote
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      down vote

      favorite











      In Theorem 5.2 in Lynche (1988) "A data reduction strategy for splines with applications to the approximation of functions and data", a bound for the difference between the $(l_2,t)$ and $L^2$ norms is given (Equation 5.8), where $(l_2,t)$ is the discrete weighted norm defined in Equation 5.4.



      Could this result be extended to the general $(l_p,t)$ and $L^p$ $(l_2,t)$ norms
      for $1leq pleqinfty$? Or at least for $p=1$?



      Thanks in advance.










      share|cite|improve this question









      New contributor




      Fabio.100 is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
      Check out our Code of Conduct.











      In Theorem 5.2 in Lynche (1988) "A data reduction strategy for splines with applications to the approximation of functions and data", a bound for the difference between the $(l_2,t)$ and $L^2$ norms is given (Equation 5.8), where $(l_2,t)$ is the discrete weighted norm defined in Equation 5.4.



      Could this result be extended to the general $(l_p,t)$ and $L^p$ $(l_2,t)$ norms
      for $1leq pleqinfty$? Or at least for $p=1$?



      Thanks in advance.







      norm approximation spline






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      edited Nov 16 at 14:36





















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      asked Nov 16 at 12:14









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