Series concatenation of 2D convolutional codes by means of input-state-output representations

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Title: Series concatenation of 2D convolutional codes by means of input-state-output representations
Authors: Climent, Joan-Josep | Napp, Diego | Pinto, Raquel | Simões, Rita
Research Group/s: Grupo de Álgebra y Geometría (GAG)
Center, Department or Service: Universidad de Alicante. Departamento de Matemáticas
Keywords: 2D convolution codes | Series concatenation | Reachability | Observability
Knowledge Area: Álgebra
Issue Date: 25-Jan-2018
Publisher: Taylor & Francis
Citation: International Journal of Control. 2018, 91(12): 2682-2691. doi:10.1080/00207179.2017.1410573
Abstract: In this paper, we investigate the properties of two-dimensional (2D) convolutional codes which are obtained from series concatenation of two 2D convolutional codes. For this purpose, we confine ourselves to dealing with finite-support 2D convolutional codes and make use of the Fornasini–Marchesini input-state-output (ISO) model representations. Within these ISO representations, we study when the structural properties of modal reachability and modal observability of the two given ISO representations carry over to the resulting 2D convolutional code. Moreover, we provide necessary conditions for obtaining a systematic concatenated convolutional code. Finally, we present a lower bound on its free distance.
Sponsor: The work of the second, third and fourth authors was supported by Portuguese funds through the Center for Research and Development in Mathematics and Applications (CIDMA); The Portuguese Foundation for Science and Technology (FCT – Fundação para a Ciência e a Tecnologia) [grant number UID/MAT/04106/2013].
URI: http://hdl.handle.net/10045/86869
ISSN: 0020-7179 (Print) | 1366-5820 (Online)
DOI: 10.1080/00207179.2017.1410573
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2018 Informa UK Limited, trading as Taylor & Francis Group
Peer Review: si
Publisher version: https://doi.org/10.1080/00207179.2017.1410573
Appears in Collections:INV - GAG - Artículos de Revistas

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