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Fredrik Gustafsson - One of the best experts on this subject based on the ideXlab platform.
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doi:10.1155/2008/147407 Research Article Downsampling Non-Uniformly Sampled Data
2013Co-Authors: Frida Eng, Fredrik GustafssonAbstract: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
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Downsampling non-uniformly Sampled data
2007Co-Authors: Frida Eng, Fredrik GustafssonAbstract: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.
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blind equalization of time errors in a time interleaved adc system
2005Co-Authors: J Elbornsson, Fredrik Gustafsson, Janerik EklundAbstract:To significantly increase the sampling rate of an analog-to-digital converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the Sampled Signal. In this paper, we present a method for estimation and compensation of the time mismatch errors. The estimation method requires no knowledge about the input Signal, except that it should be band limited to the foldover frequency /spl pi//T/sub s/ for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the time errors. The Cramer-Rao bound (CRB) for the time error estimates is also calculated and compared to Monte Carlo simulations. The estimation method has also been validated on measurements from a real time-interleaved ADC system with 16 ADCs.
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blind adaptive equalization of mismatch errors in a time interleaved a d converter system
2004Co-Authors: J Elbornsson, Fredrik Gustafsson, J E EklundAbstract:To significantly increase the sampling rate of an A/D converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the Sampled Signal. In this paper, we present a method for estimation and compensation of the mismatch errors. The estimation method requires no knowledge about the input Signal except that it should be bandlimited to the Nyquist frequency for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the mismatch errors. The estimation method has been validated with simulations and measurements from a time-interleaved ADC system.
F. N. Khan - One of the best experts on this subject based on the ideXlab platform.
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Simultaneous and Independent OSNR and Chromatic Dispersion Monitoring Using Empirical Moments of Asynchronously Sampled Signal Amplitudes
2012Co-Authors: F. N. Khan, Alan Pak Tao Lau, Trevor Anderson, Ping Kong Alexander WaiAbstract:We analytically investigate and derive equations for the empirical moments of asynchronously Sampled Signal amplitudes as functions of Signal power, noise power, and accumulated chromatic dispersion (CD) of a transmission link. The solutions of these equations enable low-cost, simultaneous and independent monitoring of in-band optical Signal-to-noise ratio (OSNR) and CD of the fiber link for various modulation formats and data rates. Numerical simulations are performed to validate the proposed technique and the results demonstrate independent OSNR and CD monitoring with good accuracy and large monitoring ranges. The influence of first-order polarization-mode dispersion (PMD) on the accuracy of the proposed monitoring technique is also investigated.
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Simultaneous and independent OSNR and chromatic dispersion monitoring using empirical moments of asynchronously Sampled Signal amplitudes
2012Co-Authors: F. N. Khan, Lau Apt, Tb Anderson, Lu C, Wai PkaAbstract:We analytically investigate and derive equations for the empirical moments of asynchronously Sampled Signal amplitudes as functions of Signal power, noise power, and accumulated chromatic dispersion (CD) of a transmission link. The solutions of these equations enable low-cost, simultaneous and independent monitoring of in-band optical Signal-to-noise ratio (OSNR) and CD of the fiber link for various modulation formats and data rates. Numerical simulations are performed to validate the proposed technique and the results demonstrate independent OSNR and CD monitoring with good accuracy and large monitoring ranges. The influence of first-order polarization-mode dispersion (PMD) on the accuracy of the proposed monitoring technique is also investigated.Department of Electronic and Information Engineerin
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Optical Performance Monitoring Using Artificial Neural Networks Trained With Empirical Moments of Asynchronously Sampled Signal Amplitudes
2012Co-Authors: F. N. Khan, Thomas Shun Rong Shen, Yudi Zhou, Chao LuAbstract:We propose a low-cost technique for simultaneous and independent optical Signal-to-noise ratio (OSNR), chromatic dispersion (CD), and polarization-mode dispersion (PMD) monitoring in 40/56-Gb/s return-to-zero differential quadrature phase-shift keying (RZ-DQPSK) and 40-Gb/s RZ-DPSK systems, using artificial neural networks (ANN) trained with empirical moments of asynchronously Sampled Signal amplitudes. The proposed technique employs an extremely simple hardware and digital Signal processing to enable multi-impairment monitoring at different data rates and for various modulation formats without necessitating hardware changes. Simulation results demonstrate wide dynamic ranges and good monitoring accuracies.
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Joint OSNR and chromatic dispersion monitoring using empirical moments of asynchronously Sampled Signal amplitudes
2011Co-Authors: F. N. Khan, Alan Pak Tao Lau, Ping Kong Alexander WaiAbstract:We propose a technique for simultaneous and independent optical Signal-to-noise ratio (OSNR) and chromatic dispersion (CD) monitoring by using the empirical moments of asynchronously Sampled Signal amplitude. The proposed technique is low-cost and is applicable to various modulation formats and data rates with good accuracy and large monitoring ranges.
Ping Kong Alexander Wai - One of the best experts on this subject based on the ideXlab platform.
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Simultaneous and Independent OSNR and Chromatic Dispersion Monitoring Using Empirical Moments of Asynchronously Sampled Signal Amplitudes
2012Co-Authors: F. N. Khan, Alan Pak Tao Lau, Trevor Anderson, Ping Kong Alexander WaiAbstract:We analytically investigate and derive equations for the empirical moments of asynchronously Sampled Signal amplitudes as functions of Signal power, noise power, and accumulated chromatic dispersion (CD) of a transmission link. The solutions of these equations enable low-cost, simultaneous and independent monitoring of in-band optical Signal-to-noise ratio (OSNR) and CD of the fiber link for various modulation formats and data rates. Numerical simulations are performed to validate the proposed technique and the results demonstrate independent OSNR and CD monitoring with good accuracy and large monitoring ranges. The influence of first-order polarization-mode dispersion (PMD) on the accuracy of the proposed monitoring technique is also investigated.
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Joint OSNR and chromatic dispersion monitoring using empirical moments of asynchronously Sampled Signal amplitudes
2011Co-Authors: F. N. Khan, Alan Pak Tao Lau, Ping Kong Alexander WaiAbstract:We propose a technique for simultaneous and independent optical Signal-to-noise ratio (OSNR) and chromatic dispersion (CD) monitoring by using the empirical moments of asynchronously Sampled Signal amplitude. The proposed technique is low-cost and is applicable to various modulation formats and data rates with good accuracy and large monitoring ranges.
J Elbornsson - One of the best experts on this subject based on the ideXlab platform.
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blind equalization of time errors in a time interleaved adc system
2005Co-Authors: J Elbornsson, Fredrik Gustafsson, Janerik EklundAbstract:To significantly increase the sampling rate of an analog-to-digital converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the Sampled Signal. In this paper, we present a method for estimation and compensation of the time mismatch errors. The estimation method requires no knowledge about the input Signal, except that it should be band limited to the foldover frequency /spl pi//T/sub s/ for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the time errors. The Cramer-Rao bound (CRB) for the time error estimates is also calculated and compared to Monte Carlo simulations. The estimation method has also been validated on measurements from a real time-interleaved ADC system with 16 ADCs.
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blind adaptive equalization of mismatch errors in a time interleaved a d converter system
2004Co-Authors: J Elbornsson, Fredrik Gustafsson, J E EklundAbstract:To significantly increase the sampling rate of an A/D converter (ADC), a time-interleaved ADC system is a good option. The drawback of a time-interleaved ADC system is that the ADCs are not exactly identical due to errors in the manufacturing process. This means that time, gain, and offset mismatch errors are introduced in the ADC system. These errors cause distortion in the Sampled Signal. In this paper, we present a method for estimation and compensation of the mismatch errors. The estimation method requires no knowledge about the input Signal except that it should be bandlimited to the Nyquist frequency for the complete ADC system. This means that the errors can be estimated while the ADC is running. The method is also adaptive to slow changes in the mismatch errors. The estimation method has been validated with simulations and measurements from a time-interleaved ADC system.
Jelena Kovačević - One of the best experts on this subject based on the ideXlab platform.
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discrete Signal processing on graphs sampling theory
2015Co-Authors: Siheng Chen, Aliaksei Sandryhaila, Rohan Varma, Jelena KovačevićAbstract:We propose a sampling theory for Signals that are supported on either directed or undirected graphs. The theory follows the same paradigm as classical sampling theory. We show that perfect recovery is possible for graph Signals bandlimited under the graph Fourier transform. The Sampled Signal coefficients form a new graph Signal, whose corresponding graph structure preserves the first-order difference of the original graph Signal. For general graphs, an optimal sampling operator based on experimentally designed sampling is proposed to guarantee perfect recovery and robustness to noise; for graphs whose graph Fourier transforms are frames with maximal robustness to erasures as well as for Erdős-Renyi graphs, random sampling leads to perfect recovery with high probability. We further establish the connection to the sampling theory of finite discrete-time Signal processing and previous work on Signal recovery on graphs. To handle full-band graph Signals, we propose a graph filter bank based on sampling theory on graphs. Finally, we apply the proposed sampling theory to semi-supervised classification of online blogs and digit images, where we achieve similar or better performance with fewer labeled samples compared to previous work.
