Some classes of burst asymmetric or unidirectional error correcting codes

In this article, the authors investigate the enhanced two stage MMSE (TS-MMSE) equalizer in bit-interleaved coded FBMC/OQAM system which gives a tradeoff between complexity and performance, since error correcting codes limits error propagation, so this allows the equalizer to remove not only ICI but also ISI in the second stage. The proposed equalizer has shown less design complexity compared to the other MMSE equalizers. The obtained results show that the probability of error is improved where SNR gain reaches 2 dB measured at BER compared with ICI cancellation for different types of modulation schemes and ITU Vehicular B channel model. Some simulation results are provided to illustrate the effectiveness of the proposed equalizer.

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Error-Correcting Codes in Projective Spaces Via Rank-Metric Codes and Ferrers Diagrams

IEEE Transactions on Information Theory ◽

10.1109/tit.2009.2021376 ◽

2009 ◽

Vol 55 (7) ◽

pp. 2909-2919 ◽

Cited By ~ 99

Author(s):

Tuvi Etzion ◽

Natalia Silberstein

Keyword(s):

Projective Spaces ◽

Error Correcting Codes ◽

Rank Metric ◽

Rank Metric Codes ◽

Ferrers Diagrams

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A robust and high capacity data hiding method for JPEG compressed images with SVD-based block selection and advanced error correcting techniques

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-189877 ◽

2021 ◽

pp. 1-11

Author(s):

Kusan Biswas

Keyword(s):

Data Hiding ◽

High Capacity ◽

Error Correcting Codes ◽

Human Vision ◽

Data Embedding ◽

Compressed Images ◽

Matrix Encoding ◽

Dct Coefficients ◽

Capacity Data ◽

Value Decomposition

In this paper, we propose a frequency domain data hiding method for the JPEG compressed images. The proposed method embeds data in the DCT coefficients of the selected 8 × 8 blocks. According to the theories of Human Visual Systems (HVS), human vision is less sensitive to perturbation of pixel values in the uneven areas of the image. In this paper we propose a Singular Value Decomposition based image roughness measure (SVD-IRM) using which we select the coarse 8 × 8 blocks as data embedding destinations. Moreover, to make the embedded data more robust against re-compression attack and error due to transmission over noisy channels, we employ Turbo error correcting codes. The actual data embedding is done using a proposed variant of matrix encoding that is capable of embedding three bits by modifying only one bit in block of seven carrier features. We have carried out experiments to validate the performance and it is found that the proposed method achieves better payload capacity and visual quality and is more robust than some of the recent state-of-the-art methods proposed in the literature.

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