Network error correction coding (NEC) has attracted a lot of attention in recent years because of its potential usefulness in network communications. Several kinds of errors may occur in communication networks using n...
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Network error correction coding (NEC) has attracted a lot of attention in recent years because of its potential usefulness in network communications. Several kinds of errors may occur in communication networks using network coding. This includes random errors, erasures, and errors caused by attacks from malicious nodes. The main goal of the theory of NEC is to deal with these errors efficiently. Two kinds of network models have been considered in network coding theory: coherent and noncoherent networks. A network is called coherent if network characteristics are known to senders and receivers, and called noncoherent if they are unknown. Although both scenarios are theoretically interesting, the noncoherent network model fits better to the requirements in most applications. So far, there are two lines of research in the theory of NEC. One approach follows the classical method by representing messages by sequences and the other approach uses the theory of rank metric codes for network error correction by representing messages by subspaces. Following both approaches, basic theories have been developed. This includes the formulation of channel models, the characterization of error correction/detection capabilities for various kinds of errors, the derivation of bounds for NECs, the study of existence and constructions of optimal codes, the development of encoding and decoding techniques, and the design of code suitable for real applications. In this paper, we summarize some important contributions in this research direction.
An algorithm for generating parity-check matrices of regular low-density paritycheck codes based on permutation matrices and Steiner triple systems S(v, 3, 2), v = 2 (m) - 1, is proposed. Estimations of the rate, mini...
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An algorithm for generating parity-check matrices of regular low-density paritycheck codes based on permutation matrices and Steiner triple systems S(v, 3, 2), v = 2 (m) - 1, is proposed. Estimations of the rate, minimum distance, and girth for obtained code constructions are presented. Results of simulation of the obtained code constructions for an iterative "belief propagation" (Sum-Product) decoding algorithm applied in the case of transmission over a binary channel with additive Gaussian white noise and BPSK modulation are presented.
Multiplexed detection technology has been attractive for its simultaneous assay of several analytes, which play significant roles in applications such as Screening for combinatorial chemistry, genetic analysis, and cl...
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Multiplexed detection technology has been attractive for its simultaneous assay of several analytes, which play significant roles in applications such as Screening for combinatorial chemistry, genetic analysis, and clinical diagnostics. This work reports a novel and potentially powerful encoding system based upon dispersible suspension arrays of multilayer rare earth core/shell nanoparticles that are capable of multiplexed, high-sensitivity reporting for biomolecule detection by the Z-contrast imaging. These nanobarcode arrays are encoded by nanostructure design based on different atomic numbers. With the Well-resolved high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) decoding technique, many thousands of unique nanobarcodes can be identified by multilayer core/shell nanostructure. Their applications to multiplexed biodetection of DNA demonstrated the highly sensitive (picomole) features of this novel nanobarcode system.
We propose a new family of one-dimensional (1D) active weight two-code keying (TCK) in spectral amplitude coding (SAC) optical code divisionmultiple access (OCDMA) networks. We use encoding and decoding transfer funct...
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We propose a new family of one-dimensional (1D) active weight two-code keying (TCK) in spectral amplitude coding (SAC) optical code divisionmultiple access (OCDMA) networks. We use encoding and decoding transfer functions to operate the 1D active weight TCK. The proposed structure includes an optical line terminal (OLT) and optical network units (ONUs) to produce the encoding and decoding codes of the proposed OLT and ONUs, respectively. The proposed ONU uses the modified cross-correlation to remove interferences from other simultaneous users, that is, the multiuser interference (MUI). When the phase-induced intensity noise (PIIN) is the most important noise, the modified cross-correlation suppresses the PIIN. In the numerical results, we find that the bit error rate (BER) for the proposed system using the 1D active weight TCK codes outperforms that for two other systems using the 1D M-Seq codes and 1D balanced incomplete block design (BIBD) codes. The effective source power for the proposed system can achieve -10 dBm, which has less power than that for the other systems.
Space-time codes built out of Alamouti components have been adopted in wireless standards such as UNITS, IEEE 802.11n, and IEEE 802.16, where they facilitate higher data rates through multiplexing of parallel data str...
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Space-time codes built out of Alamouti components have been adopted in wireless standards such as UNITS, IEEE 802.11n, and IEEE 802.16, where they facilitate higher data rates through multiplexing of parallel data streams and the addition of two or more antennas at the receiver that perform interference cancellation. This correspondence provides new theoretical insight into different algorithms for interference cancellation through a Bayesian analysis that expresses performance as a function of signal-to-noise ratio (SNR) in terms of the "angles" between different space-time coded data streams.
We propose an unsupervised word segmentation model, in which for each unlabelled sentence sample, the learning objective is to maximize the generation probability of the sentence given its all possible segmentations. ...
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We propose an unsupervised word segmentation model, in which for each unlabelled sentence sample, the learning objective is to maximize the generation probability of the sentence given its all possible segmentations. Such a generation probability can be factorized into the likelihood of each possible segment given the context in a recursive way. To capture both the long- and short-term dependencies, we propose to use a bi-directional neural language model to better extract the features of the segment's context. Two decoding algorithms were also developed to combine the context features from both directions to generate the final segmentation at the inference time, which helps to reconcile word-boundary ambiguities. Experimental results show that our context-sensitive unsupervised segmentation model achieved state-of-the-art at different evaluation settings on various datasets for Chinese, and the comparable result for Thai.
We propose a simple decoder for a widely used array code, known as the EVENODD code, which is originally designed to correct phased burst errors, to make it useful for correcting nonphased errors. The proposed scheme ...
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We propose a simple decoder for a widely used array code, known as the EVENODD code, which is originally designed to correct phased burst errors, to make it useful for correcting nonphased errors. The proposed scheme is capable of correcting almost all bursts up to a certain length. We show that the failure rate is sufficiently small and approaches zero as the block length increases. The redundancy of the code is twice the maximal burst length, which is a lower bound for the redundancy of a true burst-error-correcting code. Both the encoder and the decoder have very low complexity, both in terms of number of operations and in terms of computer code size.
We present a new decoding algorithm based on error locating pairs and correcting an amount of errors exceeding half the minimum distance. When applied to Reed-Solomon or algebraic geometry codes, the algorithm is a re...
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We present a new decoding algorithm based on error locating pairs and correcting an amount of errors exceeding half the minimum distance. When applied to Reed-Solomon or algebraic geometry codes, the algorithm is a reformulation of the so-calledpower decodingalgorithm. Asymptotically, it corrects errors up to Sudan's radius. In addition, this new framework applies to any code benefiting from an error locating pair. Similarly to Pellikaan's and Kotter's approach for unique algebraic decoding, our algorithm provides a unified point of view for decoding codes with an algebraic structure beyond the half minimum distance. It permits to get an abstract description of decoding using only codes and linear algebra and without involving the arithmetic of polynomial and rational function algebras used for the definition of the codes themselves. Such algorithms can be valuable for instance for cryptanalysis to construct a decoding algorithm of a code without having access to the hidden algebraic structure of the code.
This article deals with modelization of industrial process by using hidden Markov model. The process is seen as a discrete event system. We propose different structures based on Markov automata, called topologies. A s...
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This article deals with modelization of industrial process by using hidden Markov model. The process is seen as a discrete event system. We propose different structures based on Markov automata, called topologies. A synthetic hidden Markov model is designed in order to match to a real industrial process. The models are intended to decode industrial maintenance observations (also called "symbol"). Symbols are produced with a corresponding degradation level (also called "state"). These 2-tuple (symbol, state) are known as Markov chains, also called "a signature." Hence, these various 2-tuple are implemented in the proposed topologies by using the Baum-Welch learning algorithm (decoding by forward variable) and the segmental K-means learning (decoding by Viterbi). We assess different frameworks (topology, learning and decoding algorithm, distribution) by relevancy measurements on model outputs. Then, we determine the most relevant framework for use in maintenance activities. Afterward, we try to minimize the size of the learning data. Thus, we could evaluate the model by using "sliding windows" of data. Finally, an industrial application is developed and compared with this framework. Our goal is to improve worker safety, maintenance policy, process reliability and reduce CO2 emissions in the industrial sector.
We consider MIMO communication systems with Rayleigh fading. We propose a new coded modulation based on orthogonal sequences and state a new decodability condition. We introduce concepts and constructions of permutati...
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We consider MIMO communication systems with Rayleigh fading. We propose a new coded modulation based on orthogonal sequences and state a new decodability condition. We introduce concepts and constructions of permutation free (PF) and permutation and repetition free (PRF) codes. We also propose a construction of PRF codes with sign manipulation, whose code rate can exceed 1. For better analysis and construction of these codes we introduce a one-to-one mapping that transforms signal matrices to vectors over a finite field. We propose construction algorithms for PF and PRF codes. We build PF and PRF codes with large cardinality, which in several case achieve the maximum cardinality. Simulation of the constructed codes and estimation of their performance was done in Simulink environment. Results show high error-correcting capability, which often reaches that of STBC codes with full transmit diversity.
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