Correction Structures for Linear Weakly Time-Varying Systems

Soudan, Michael; Vogel, Christian

doi:10.1109/tcsi.2012.2185308

Cited by 10 publications

(14 citation statements)

References 41 publications

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“…The modification was presented for the Richardson iteration and its utilization for post-and pre-linearization was discussed in detail. It was shown that the resulting method is a generalization of the equalizer for linear weakly time-varying systems in [21] and that it may be regarded as a generalization of the post-linearizer in [13] and the P th-order inverse. Due to the iterative structure of the proposed linearizers, their computational cost scales with the required accuracy via the employed number of iterations.…”

Section: Discussionmentioning

confidence: 99%

“…As the corresponding structural modifications equal those for the method in [21], a detailed discussion thereof is omitted here (see also Section VII-A).…”

Section: Conditions For Convergencementioning

confidence: 99%

“…In particular, if the Volterra system H n comprises only a linear (first-order) kernel, the Richardson equalizer equals the iteration in [21]. Furthermore, for a linear system the condition for convergence in (25) reduces to the criterion provided in [21].…”

Section: A Equalization Of Linear Weakly Time-varying Systemsmentioning

confidence: 99%

“…4 The approach below is an adaptation of the corresponding proof for the time-invariant continuous-time Volterra series in [33]. Let x and x (r) be two input vectors, where the difference is given by e (r) in (21). Furthermore, let…”

Section: Appendix B Lipschitz Continuity Of a Time-varying Discrete-tmentioning

confidence: 99%

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Linearization of Time-Varying Nonlinear Systems Using A Modified Linear Iterative Method

Hotz

Vogel

2014

IEEE Trans. Signal Process.

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The linearization of nonlinear systems is an important digital enhancement technique. In this paper, a real-time capable post-and pre-linearization method for the widely applicable time-varying discrete-time Volterra series is presented. To this end, an alternative view on the Volterra series is established, which enables the utilization of certain modified linear iterative methods for linearization. For one particular linear iterative method, the Richardson iteration, the corresponding post-and pre-linearizers are discussed in detail. It is motivated that the resulting algorithm can be regarded as a generalization of some existing methods. Furthermore, a simply verifiable condition for convergence is presented, which allows the straightforward evaluation of applicability. The proposed method is demonstrated by means of the linearization of a time-varying nonlinear amplifier, which highlights its capability of linearizing significantly distorted signals, illustrates the advantageous convergence behavior, and depicts its robustness against modeling errors.

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Section: Discussionmentioning

confidence: 99%

“…As the corresponding structural modifications equal those for the method in [21], a detailed discussion thereof is omitted here (see also Section VII-A).…”

Section: Conditions For Convergencementioning

confidence: 99%

Section: A Equalization Of Linear Weakly Time-varying Systemsmentioning

confidence: 99%

Section: Appendix B Lipschitz Continuity Of a Time-varying Discrete-tmentioning

confidence: 99%

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Linearization of Time-Varying Nonlinear Systems Using A Modified Linear Iterative Method

Hotz

Vogel

2014

IEEE Trans. Signal Process.

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“…The common factor is that the information found in the output y is used to improve the input, but the algorithm is not necessarily similar to (3.1). One application where iterative solutions are often used is analog-to-digital converter (adc) correction, such as in Soudan and Vogel [2012].…”

Section: Iterative Learning Controlmentioning

confidence: 99%

Inverse system identification with applications in predistortion

Jung

2019

Linköping Studies in Science and Technology. Dissertations

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Life is not easy. Finishing a PhD is not easy. One of the good things about the PhD is that you get a chance at the end to say thank you to the people who have helped you, which you might not get in life. This is my attempt to thank the ones who have helped me go through with this project. I'll start and end these acknowledgments with people without whom I think there would be no thesis (or not this, my thesis at least, others might still be able to write theirs). To my supervisor Dr. Martin Enqvist: I think I would have given up a long time ago if it wasn't for your encouragements. I am really impressed with how you always have time (or rather, take the time) to answer questions or concerns, and without feeling stressed. I know you have lots of other things to do and I really appreciate it. I also like how you can turn things around for a positive spin. Thank you for pushing me through this! Prof. Lennart Ljung and Prof. Torkel Glad, thanks for being co-supervisors and providing input. I should have talked, asked and learned more! I have had the pleasure of having three different bosses, who have all helped me sort out the work situation when life gets in the way. Prof. Lennart Ljung, Prof. Svante Gunnarsson and Dr. Martin Enqvist, you all seem to be able to guide the group forward as well as see the people and how to help. Lennart, thanks for letting me join the group! Svante, without your flexibility and willingness to adapt I could not have finished this thesis. Thank you! Martin, thanks for making every day bring-your-baby-to-work ! I am also grateful for the administrative help from Ninna Stensgård and her predecessor Åsa Karmelind. The upside of being on the slow side finishing your PhD is that you get to meet a lot of colleagues. I have really appreciated the Automatic control group and the amazing people in it! It is a group full of brilliant, fun, and hard working people, thank you all! I think my current office mate Kerstin is my favorite, but Patrik Leissner, Maryam Sadeghi Reineh and Gustaf Hendeby, you tie for second place (and you were all far less demanding)! Many colleagues I also consider friends and hope I will still see a lot of you in the future. Special shout outs to Manon Kok (for staying in touch and being a good friend), Daniel Petersson (for pepp and believing in me), Patrik Leissner (for friendship and helpfulness

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Linearly time-varying systems and their fast implementation

Candogan,

Ozaktas

2023

Digital Signal Processing

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Correction Structures for Linear Weakly Time-Varying Systems

Cited by 10 publications

References 41 publications

Linearization of Time-Varying Nonlinear Systems Using A Modified Linear Iterative Method

Linearization of Time-Varying Nonlinear Systems Using A Modified Linear Iterative Method

Inverse system identification with applications in predistortion

Linearly time-varying systems and their fast implementation

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