Numerical Functional Analysis and Optimization

نویسنده

  • Massimo Fornasier
چکیده

In signal processing, discrete convolutions are usually involved in fast calculating coefficients of time-frequency decompositions like wavelet and Gabor frames. Depending on the regularity of the mother analyzing functions, one wants to detect the right resolution in order to achieve good approximations of coefficients. Local–global conditions on functions in order to get the convergence rate of Riemann-type sums to their scalar products in L are presented. Wiener amalgam spaces, in particular WðC , l Þ for the space-time domain and WðL, lÞ for the frequency domain, give natural norms in order to estimate errors. In particular, relations between the rate of convergence of these series to integrals by increasing resolution and the (minimal) required Besov regularity are presented by means of functional and harmonic analysis techniques.

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تاریخ انتشار 2008