Mohamed Neji Maatouk, Majd Bellaj, Najoua Essoukri Ben Amara · 2010
The ancient documents have a major importance in the history of every people and every nation. These documents involve important information that many people need. As a consequence, it is necessary to preserve these documents in order to build a numerical library in the service of the public. Therefore, the necessity of digitizing these documents permits the simultaneous access to the same documents and provides the possibility of the reproduction of these documents existing most of the time in just one example. This task is considered as an important step in the research domain. In fact, many researches have been invested for the processing, compression, segmentation and indexation of these documents. Nevertheless, with a numerical form, there is a threat of hacking, stocking, copying, modifying and finally diffusing these documents in an illegal way without losing their quality. As a consequence, we face the problem of losing the intellectual property because of the lack of methods that concern the protection of data. In order to prevent these frauds, watermarking represents a promising method to protect these images. In this context, our work makes part of protecting ancient documents essentially. In this paper, we have proposed the method of watermarking ancient documents. This method is based on the Wavelet Packet Transform (WPT) and it provides a good robustness which can face different attacks like signal processing (noise, filter and compression) and noticeable signature invisibility.
Cited by 3
Junmei Chen, Hao Chen, Zongpeng Li · 2021
By establishing a single parity check relationship between convolutional codewords, a concatenated code, termed single parity check convolutional code (SPC-CC), is proposed. By jointly en/decoding the SPC and CC, as well as carefully allocating redundant information between the pair, we can improve BER more promptly during iterative decoding. Each codeword in SPC-CC consists of only one SISO decoder, which generates one extrinsic information. The key is to simulate another using extrinsic information from other decoders. Then iteratively feed back extrinsic information to each other in a manner similar to a Turbo engine. We design en/decoding scheme of the SPC-CC, and then analyze its performance and complexity. Simulation results show that SPC-CC can effectively improve communication reliability with a moderate complexity. In addition, thanks to SPC code, SPC-CC can correct packet erasures due to fading or interference.
Cited by 0
Maurizio Martina, Mario Nicola, Guido Masera · Journal of Circuits Systems and Computers · 2009
A VLSI encoder and decoder implementation for the IEEE 802.16 WiMax convolutional turbo code is presented. Architectural choices employed to achieve high throughput, while granting a limited occupation of resources, are addressed both for the encoder and decoder side, including also the subblock interleaving and symbol selection functions specified in the standard. The complete encoder and decoder architectures, implemented on a 0.13 μm standard cell technology, sustain a decoded throughput of more than 90 Mb/s with a 200 MHz clock frequency. The encoder has the complexity of 9.2 kgate of logic and 187.2 kbit of memory, whereas the complete decoder requires 167.7 kgate and 1163 kbit.
Cited by 4
Ningquan Wang, Ruxiu Liu, A. Fatih Sarioglu · 2018
Cited by 0
Marco Chiani, Andrea Conti, Velio Tralli · IEEE Transactions on Information Theory · 2004
This correspondence presents results of code search for convolutional codes over block-fading channels (BFCs). Search criteria are based on a union bound approach which exploits the concept of generalized transfer function (GTF) of the error trellis diagram. A new asymptotic bound is derived, and the performance of the codes found using our search criterion is compared analytically and by numerical simulation with already existing codes.
Cited by 33
Siev, B., Statman, J., Rabkin, J. · NASA STI Repository (National Aeronautics and Space Administration)
The Big Viterbi Decoder (BVD), capable of decoding convolutional codes with constraint lengths of up to 15, is under development for the Deep Space Network (DSN). As part of the development, a commercial single-chip (7,1/2) Viterbi decoder is used to enable early start of system integration. Tests of the integrated partial system (including simulator, input systems, output interfaces, and computer controls) were recently completed at the DSN Compatibility Test Area (CTA-21) at JPL. The system elements used for the demonstration and test results are described.
Cited by 0Open access
Al-Qudah, Muhammed · OpenMETU (Middle East Technical University) · 2019
Cited by 0
Igor Zhilin, Victor Zyablov, D. K. Zigangirov · Electronic Notes in Discrete Mathematics · 2017
Cited by 3
M.-L. de Mateo · 2002
A node synchronization technique which applies in general to any 1/n rate convolutional code is described. The proposed method makes statistical decisions about node synchronisation based on the hard-quantized undecoded data stream. It is based on a node synchronisation scheme previously suggested by G. Lorden et al. (1984) for the standard rate 1/2, constraint length 7, convolutional code. Two examples illustrating the generalized synchronisation technique for code rates 1/3 and 1/4 are given. Particularly, it is shown that the performance of the method is significantly worse for code rates 1/3 and 1/4 than for the 1/2 rate code.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Cited by 4
Xiaoqing Ma · DEStech Transactions on Computer Science and Engineering · 2017
This paper completes the design of control system simulation of convolutional code error based on MATLAB software platform, the convolution encoding the input signal through the AWGN channel transmission, the receiver decodes the statistical transmission error rate, different rate and different SNR BER statistics under the receiver. The practice shows that the smaller the bit rate, the smaller the interference and the smaller bit error rate, and the higher the signal-to-noise ratio, the smaller the bit error rate.
Cited by 0Open access
Jessica Moore, Ben Gelman, David Slater · 2019
Descriptive comments play a crucial role in the software engineering process. They decrease development time, enable better bug detection, and facilitate the reuse of previously written code. However, comments are commonly the last of a software developer’s priorities and are thus either insufficient or missing entirely. Automatic source code summarization may therefore have the ability to significantly improve the software development process. We introduce a novel encoder-decoder model that summarizes source code, effectively writing a comment to describe the code’s functionality. We make two primary innovations beyond current source code summarization models. First, our encoder is fully language-agnostic and requires no complex input preprocessing. Second, our decoder has an open vocabulary, enabling it to predict any word, even ones not seen in training. We demonstrate results comparable to state-of-the-art methods on a single-language data set and provide the first results on a data set consisting of multiple programming languages.
Cited by 17
Kohei Yamauchi, Hiroyuki Kobayashi · The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) · 2020
In this paper, the author aims to embed arbitrary information in arbitrary images and restore them using convolutional neural networks. To achieve this goal, we propose two sets of CNN models for embedding and restoring information in images.Thanks to the error correction nature of QR code, embedded information is expected to be restored without errors. However, in the previous model, the proposed method could only be applied to blurred images. This time, the model has been improved so that the QR code can be embedded in a high-resolution image and restored.
Cited by 0
2016
Abstract. As to the problem of blind recognition for convolutional code, the existing recognitory methods ’ principle and process are summarized, and they are simulated and analyzed with Matlab. Four methods are introduced for the recognition of generation polynomials, and the comparison of these methods shows that the Euclidean algorithm works better at low BER, while the method based Walsh-Hadamard transform has a better accuracy when BER is as high as 10-2.
Cited by 0
Gabriel Vargas-Monroy, Daissi-Bibiana Gonzalez-Roldan, Carlos Montenegro et al. · Frontiers in Artificial Intelligence · 2025
The results demonstrate the effectiveness of employing computer vision and deep learning techniques to process images and extract relevant information. The infrastructure is designed based on a modular approach employing Celery and Redis, enabling the system to manage asynchronous tasks efficiently. The implementation of image recognition, text analysis, and neural network construction yields promising outcomes in generating source code from diagrams. Despite some challenges related to hardware limitations during the training of the neural network, the system successfully interprets the diagrams and produces artifacts using the MDA approach. Plugins and DSLs enhance flexibility by supporting various programming languages and automating code deployment on platforms such as GitHub and Heroku.
Cited by 1Open access
Xiao Ma, Wenchao Lin, Suihua Cai et al. · 2019
This paper is concerned with block Markov superposition transmission (BMST) of tail-biting convolutional code (TBCC). We propose a new decoding algorithm for BMST-TBCC, which integrates a serial list Viterbi algorithm (SLVA) with a soft check instead of conventional cyclic redundancy check (CRC). The basic idea is that, compared with an erroneous candidate codeword, the correct candidate codeword for the first sub-frame has less influence on the output of Viterbi algorithm for the second sub-frame. The threshold is then determined by statistical learning based on the introduced empirical divergence function. The numerical results illustrate that, under the constraint of equivalent decoding delay, the BMST-TBCC has comparable performance with the polar codes. As a result, BMST-TBCCs may find applications in the scenarios of the streaming ultra-reliable and low latency communication (URLLC) data services.
Cited by 9
Jessica Moore, Ben Gelman, David Slater · arXiv (Cornell University) · 2019
Descriptive comments play a crucial role in the software engineering process. They decrease development time, enable better bug detection, and facilitate the reuse of previously written code. However, comments are commonly the last of a software developer's priorities and are thus either insufficient or missing entirely. Automatic source code summarization may therefore have the ability to significantly improve the software development process. We introduce a novel encoder-decoder model that summarizes source code, effectively writing a comment to describe the code's functionality. We make two primary innovations beyond current source code summarization models. First, our encoder is fully language-agnostic and requires no complex input preprocessing. Second, our decoder has an open vocabulary, enabling it to predict any word, even ones not seen in training. We demonstrate results comparable to state-of-the-art methods on a single-language data set and provide the first results on a data set consisting of multiple programming languages.
Cited by 4Open access
Lerina Aversano, Mario Luca Bernardi, Marta Cimitile et al. · Lecture notes in computer science · 2022
Cited by 1
Bin Li · SHILAP Revista de lepidopterología · 2021
Automatic code comment generation technology can analyze the semantic information of source code and generate corresponding natural language descriptions,which can help developers understand the program and reduce the time cost during software maintenance.Most of the existing technologies are based on the encoder and decoder model of the recurrent neural network(RNN).However,this method suffers from long-term dependency problem,which means it cannot generate high-quality comments when analyzing far-away code blocks.To solve this problem,this paper proposes an automatic code comment generation method,which uses the convolutional neural network(CNN) to alleviate the inaccurate comments information caused by the long-term dependence problem.More specifically,this paper uses two CNNs,one source-code based CNN and one AST-based CNN,to capture source code's semantic information.The experimental results indicate that,compared to the two most recent methods,DeepCom and Hybrid-DeepCom,the method proposed in this paper generates more useful code comments and takes less time to execute.
Cited by 2Open access
Mounika. M, Srihari Piratla · 2025
Cited by 0
J. Bibb Cain, Robert W. Boyd · 1978
Cited by 1