The Experts below are selected from a list of 15 Experts worldwide ranked by ideXlab platform

Fredrik Gustafsson - One of the best experts on this subject based on the ideXlab platform.

  • doi:10.1155/2008/147407 Research Article Downsampling Non-Uniformly Sampled Data
    2013
    Co-Authors: Frida Eng, Fredrik Gustafsson
    Abstract:

    Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with Normalized Cutoff Frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the Frequency domain using the fast Fourier transform (FFT) algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate nonuniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the intersample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third Frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process. Copyright © 2008 F. Eng and F. Gustafsson. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1

  • Downsampling non-uniformly sampled data
    2007
    Co-Authors: Frida Eng, Fredrik Gustafsson
    Abstract:

    Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with Normalized Cutoff Frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the Frequency domain using the fast Fourier transform (FFT) algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate non-uniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the intersample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third Frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process.

Frida Eng - One of the best experts on this subject based on the ideXlab platform.

  • doi:10.1155/2008/147407 Research Article Downsampling Non-Uniformly Sampled Data
    2013
    Co-Authors: Frida Eng, Fredrik Gustafsson
    Abstract:

    Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with Normalized Cutoff Frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the Frequency domain using the fast Fourier transform (FFT) algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate nonuniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the intersample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third Frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process. Copyright © 2008 F. Eng and F. Gustafsson. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1

  • Downsampling non-uniformly sampled data
    2007
    Co-Authors: Frida Eng, Fredrik Gustafsson
    Abstract:

    Decimating a uniformly sampled signal a factor D involves low-pass antialias filtering with Normalized Cutoff Frequency 1/D followed by picking out every Dth sample. Alternatively, decimation can be done in the Frequency domain using the fast Fourier transform (FFT) algorithm, after zero-padding the signal and truncating the FFT. We outline three approaches to decimate non-uniformly sampled signals, which are all based on interpolation. The interpolation is done in different domains, and the intersample behavior does not need to be known. The first one interpolates the signal to a uniformly sampling, after which standard decimation can be applied. The second one interpolates a continuous-time convolution integral, that implements the antialias filter, after which every Dth sample can be picked out. The third Frequency domain approach computes an approximate Fourier transform, after which truncation and IFFT give the desired result. Simulations indicate that the second approach is particularly useful. A thorough analysis is therefore performed for this case, using the assumption that the non-uniformly distributed sampling instants are generated by a stochastic process.

M Kotenko - One of the best experts on this subject based on the ideXlab platform.

Barahona Varela Fabián - One of the best experts on this subject based on the ideXlab platform.

  • Cálculo de las frecuencias de corte en fibras ópticas de índice escalonado, utilizando MATLAB
    2012
    Co-Authors: Bastidas Mora, Henry Arturo, Barahona Varela Fabián
    Abstract:

    The math analysis of propagation modes and other relevant operating parameters to waveguides and optical fibers can be found by solving the four equations of Maxwell, and also meeting effectively boundary conditions analyzed for each case according to geometry and materials they are produced with. These solutions however are quite difficult and sometimes confusing for students who use them first time. In this paper we developed and implemented an application using Matlab tool, which provides students and teachers the procedure and calculations carried out to get some parameters, such as numerical aperture, Normalized Cutoff Frequency and actual Cutoff Frequency to step-index optical fibers based on refractive indices and a core radius.El análisis matemático de los modos de propagación y de otros parámetros importantes de operación de las guías de onda y las fibras ópticas se puede encontrar al resolver las cuatro ecuaciones de Maxwell y satisfacer adecuadamente las condiciones de frontera en cada caso analizado de acuerdo con su geometría y los materiales con los cuales esté constituido. Sin embargo, estas soluciones resultan muy laboriosas y a veces confusas para los estudiantes que las enfrentan por primera vez. En el presente trabajo se desarrolló e implementó una aplicación utilizando la herramienta Matlab que facilita a los estudiantes y docentes, el procedimiento y los cálculos que se llevan a cabo para obtener algunos parámetros como la apertura numérica, frecuencia de corte normalizada y frecuencia de corte normal para las fibras ópticas de índice escalonado, partiendo de los índices de refracción y el radio del núcleo

Bastidas Mora, Henry Arturo - One of the best experts on this subject based on the ideXlab platform.

  • Cálculo de las frecuencias de corte en fibras ópticas de índice escalonado, utilizando MATLAB
    2012
    Co-Authors: Bastidas Mora, Henry Arturo, Barahona Varela Fabián
    Abstract:

    The math analysis of propagation modes and other relevant operating parameters to waveguides and optical fibers can be found by solving the four equations of Maxwell, and also meeting effectively boundary conditions analyzed for each case according to geometry and materials they are produced with. These solutions however are quite difficult and sometimes confusing for students who use them first time. In this paper we developed and implemented an application using Matlab tool, which provides students and teachers the procedure and calculations carried out to get some parameters, such as numerical aperture, Normalized Cutoff Frequency and actual Cutoff Frequency to step-index optical fibers based on refractive indices and a core radius.El análisis matemático de los modos de propagación y de otros parámetros importantes de operación de las guías de onda y las fibras ópticas se puede encontrar al resolver las cuatro ecuaciones de Maxwell y satisfacer adecuadamente las condiciones de frontera en cada caso analizado de acuerdo con su geometría y los materiales con los cuales esté constituido. Sin embargo, estas soluciones resultan muy laboriosas y a veces confusas para los estudiantes que las enfrentan por primera vez. En el presente trabajo se desarrolló e implementó una aplicación utilizando la herramienta Matlab que facilita a los estudiantes y docentes, el procedimiento y los cálculos que se llevan a cabo para obtener algunos parámetros como la apertura numérica, frecuencia de corte normalizada y frecuencia de corte normal para las fibras ópticas de índice escalonado, partiendo de los índices de refracción y el radio del núcleo