Effect Of Error Propagation Research Articles

A Variable Leaky Entropy-Based Whitening Algorithm for Blind Decision Feedback Equalization

This paper addresses the joint entropy maximization algorithm constrained by the variable leaky factor (JEM-VL) aiming at mitigating the feedback filter (FBF) mismatch effects characterizing the operation of the decision feedback equalizer which, at the start of adaptation, swaps positions of feedforward and feedback filters so that the latter acts as a linear all-pole whitener of the received signal. The FBF mismatch is a result of disparity between the FBF setup achieved in the blind mode by observing channel outputs and an excepted FBF setup in the tracking mode which is driven by detected data symbols. Depending on the given signal complexity and inter-symbol interference severity, the FBF filter mismatch is typically manifested by the equalizer convergence instability or even the catastrophic error propagation effects arising at the time of the equalizer structure-criterion switching from the blind to the tracking operation mode. The constraint of superfluous coefficients of the FBF filter by means of the JEM-VL algorithm eliminates the equalizer convergence instability at the time of its switching and, consequently, increases equalization successfulness. The efficiency of the JEM-VL algorithm is verified by simulations using the 64-QAM signal.

A Comprehensive Error Analysis Method for Accuracy Reliability Deployment

To avoid equipment accuracy failure caused by degradation with use, the concept of Reliability Function Deployment (RFD) is employed to set up a comprehensive error analysis model. An operative matrix tool, called the House of Accuracy Reliability (HoAR) is presented. The HoAR is combined with Fault Tree Analysis (FTA), Failure Mode Effects and Criticality Analysis (FMECA) and Quality Function Deployment (QFD). In the HoAR, besides geometric error, thermal deformation error and load deformation error, a domino effect of error propagation is also taken into account for the risk assessment. Using the results from the HoAR, a comprehensive error analysis can be easily performed, making it possible to identify the significant accuracy parameters and compensate for the accuracy losses. Tests on a numerical control lathe are carried out to validate the proposed model and method.

Iterative Channel Estimation for MIMO-OFDM System in Fast Time-Varying Channels

A practical iterative channel estimation technique is proposed for the multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) system in the high-speed mobile environment, such as high speed railway scenario. In the iterative algorithm, the Kalman filter and data detection are jointed to estimate the time-varying channel, where the detection error is considered as part of the noise in the Kalman recursion in each iteration to reduce the effect of the detection error propagation. Moreover, the employed Kalman filter is from the canonical state space model, which does not include the parameters of the autoregressive (AR) model, so the proposed method does not need to estimate the parameters of AR model, whose accuracy affects the convergence speed. Simulation results show that the proposed method is robust to the fast time-varying channel, and it can obtain more gains compared with the available methods.

Likelihood re-ordering and feedback correction for reduced error propagation in decision-feedback schemes via difference equations

A decision correction scheme is proposed to replace the unconfident decisions in the feedback loops to mitigate the effect of error propagation in a decision feedback scheme. A likelihood based reliability ordering is also introduced to further improve the reliability of feedback stages. With a negligible additional complexity cost, the proposed scheme is able to effectively mitigate the error propagation and achieve significant performance gains.

Error Propagation in Isometric Log-ratio Coordinates for Compositional Data: Theoretical and Practical Considerations.

Compositional data, as they typically appear in geochemistry in terms of concentrations of chemical elements in soil samples, need to be expressed in log-ratio coordinates before applying the traditional statistical tools if the relative structure of the data is of primary interest. There are different possibilities for this purpose, like centered log-ratio coefficients, or isometric log-ratio coordinates. In both the approaches, geometric means of the compositional parts are involved, and it is unclear how measurement errors or detection limit problems affect their presentation in coordinates. This problem is investigated theoretically by making use of the theory of error propagation. Due to certain limitations of this approach, the effect of error propagation is also studied by means of simulations. This allows to provide recommendations for practitioners on the amount of error and on the expected distortion of the results, depending on the purpose of the analysis.

Iterative sequential Monte Carlo algorithm for motif discovery

The discovery of motifs in transcription factor binding sites is important in the transcription process, and is crucial for understanding the gene regulatory relationship and evolution history. Identifying weak motifs and reducing the effect of local optima, error propagation and computational complexity are still important, but challenging tasks for motif discovery. This study proposes an iterative sequential Monte Carlo (ISMC) motif discovery algorithm based on the position weight matrix and the Gibbs sampling model to locate conserved motifs in a given set of nucleotide sequences. Three sub-algorithms have been proposed. Algorithm 1 (see Fig. 1) deals with the case of one motif instance of fixed length in each nucleotide sequence. Furthermore, the proposed ISMC algorithm is extended to deal with more complex situations including unique motif of unknown length in Algorithm 2, unique motif with unknown abundance in Algorithm 3 (see Fig. 2) and multiple motifs. Experimental results over both synthetic and real datasets show that the proposed ISMC algorithm outperforms five other widely used motif discovery algorithms in terms of nucleotide and site-level sensitivity, nucleotide and site-level positive prediction value, nucleotide-level performance coefficient, nucleotide-level correlation coefficient and site-level average site performance.

Reliable scalable video streaming using layer weight switching‐based unequal Luby transform

A layer weight switching-based unequal Luby transform (LWS-ULT) method is proposed to minimise video distortion over packet-lossy networks. The proposed ULT method divides all quality layers into more important set (MIS) and less important set to provide unequal packet protection property in LT codes based on error propagation effects. The number of quality layer in MIS is adjusted in accordance with channel status. At high packet loss rate, lower number of quality layer is assigned into MIS for more protection of quality layer with larger error propagation weight. On the other hand, higher number of quality layer is included in MIS for improving video quality by expanding the range of protection at low packet loss rate. Simulation results demonstrate that the proposed LWS-ULT method gives robust performance and significantly improved video quality (0.9–1.2 dB in Y-PSNR), compared with the conventional ULT schemes.

Low-Density Lattice Coded Relaying With Joint Iterative Decoding

Low-density lattice codes (LDLCs) are known for their high decoding efficiency and near-capacity performance on point-to-point Gaussian channels. In this paper, we present a distributed LDLC-based cooperative relaying scheme for the multiple-access relay channel (MARC). The relay node decodes LDLC-coded packets from two sources and forwards a network-coded combination to the destination. At the destination, a joint iterative decoding structure is designed to exploit the diversity gain as well as coding gain. For the LDLC-based network coding operation at the relay, we consider two alternative methods which offer a tradeoff between implementation complexity and performance, called superposition LDLC (S-LDLC) and modulo-addition LDLC (MA-LDLC). Soft symbol relaying is considered as an alternative to hard decision relaying which is capable of reducing the effect of error propagation at the relay. Simulation results show that the proposed scheme can provide greater diversity gain and up to 6.2 dB coding gain when compared with noncooperative LDLC coding and uncoded network-coded transmission. The proposed scheme also achieves 2.5 dB gain over network-turbo-coded cooperation, for the same code rate and overall transmitted power. Also, soft symbol relaying is shown to provide approximately 2 dB gain over hard decision relaying when the source-relay link suffers from deep fading.

Efficient and robust phase unwrapping algorithm based on unscented Kalman filter, the strategy of quantizing paths-guided map, and pixel classification strategy.

This paper presents an efficient and robust phase unwrapping algorithm which combines an unscented Kalman filter (UKF) with a strategy of quantizing a paths-guided map and a pixel classification strategy based on phase quality information. The advantages of the proposed method depend on the following contributions: (1) the strategy of quantizing the paths-guided map can accelerate the process of searching unwrapping paths and greatly reducing time consumption on the unwrapping procedure; (2) the pixel classification strategy proposed by this paper can reduce the error propagation effect by decreasing the amounts of pixels with equal quantized paths-guided value in the process of unwrapping; and (3) the unscented Kalman filter enables simultaneous filtering and unwrapping without the information loss caused by linearization of a nonlinear model. In addition, a new paths-guided map derived from a phase quality map is inserted into the strategy of quantizing the paths-guided map to provide a more robust path of unwrapping, and then ensures better unwrapping results. Results obtained from synthetic data and real data show that the proposed method can efficiently obtain better solutions with respect to some of the most used algorithms.

Land use mapping error introduces strongly-localised, scale-dependent uncertainty into land use and ecosystem services modelling

We analysed the impact of land use mapping error on uncertainty in projections of land use and ecosystem services in Australia's agricultural land from 2013 to 2050. We simulated land use mapping error at four levels then modelled potential land use transitions and indicators of ecosystem services supply using the Land Use Trade-Offs (LUTO) model. Increasing error resulted in larger areas of uncertainty in land use transition. This influence was highly localised, with concentrations in mixed cropping areas, rather than homogeneous extensive grazing areas. Error effects also varied with spatial scale. While barely discernible when aggregated at the national level, error effects increased markedly with granularity of assessment. Sensitivity to land use mapping error also differed between ecosystem services. The results were driven largely by geographic heterogeneity and nuance in the environmental and economic drivers of land use peculiar to the study area. The finding of strongly-localised, scale-dependent impacts that differed between ecosystem services is likely to hold for other areas. Understanding the effects of land use mapping error propagation is necessary both for guiding efforts to reduce mapping error, and for supporting policy and governance at multiple scales.

Aircraft Design Optimization with Uncertainty Based on Fuzzy Clustering Analysis

AbstractUncertainty always exists in any design problems; conventional aircraft design with deterministic optimization may achieve underdesign or overdesign. Therefore, it is necessary to consider uncertainty analysis in aircraft concept design. Traditional uncertainty analyses need many sampling points to simulate the uncertain models. These methods include a large number of calculations to achieve the required accuracy. To increase the efficiency of uncertainty analysis and reduce the effect of error propagation on uncertainty models, a method with dynamic surrogate models based on fuzzy clustering analysis is proposed in this paper. Among the design spaces, the sampling points with little influence on response surface are abandoned by dynamic screening until the surrogate model reaches the expected level of accuracy. This method is applied to the optimization of a hypothetical aircraft concept design, which shows that the calculated amount of uncertainty analysis can be reduced effectively while the op...

Scalable Video Transmission Over Wireless Networks Based on Loss Distribution and Layer Information

We propose an efficient scalable video transmission method using unequal forward error correction (FEC) scheme based on loss distribution and layer information. The actual packet loss rates over wireless networks are variable due to the clustered packet losses. First, we deduce the expected packet loss recovery rate from the estimation of the effective packet loss rate using loss distribution statistics. Second, layer-based distortion metric is presented including error propagation effects from hierarchical prediction structure in compressed scalable video packets. Third, the performance metric for FEC assignment is proposed from the layer-based distortion metric and the expected packet loss recovery rate. Finally, the FEC assignment algorithm is proposed for maximizing the performance metric. The proposed unequal FEC assignment method demonstrates robustness and significantly improved performance for scalable video transmission in various channel conditions compared to previous FEC assignment schemes.

Relay selection for DF-based cooperative vehicular systems

In this paper, error performance analysis of decode-and-forward (DF)-based cooperative vehicular networks with relay selection is investigated. All of the links in the system are modeled as cascaded Nakagami-m distributed random variables which provide a realistic description of an intervehicular channel. We employ virtual-noise (VN)-based demodulation, maximum likelihood (ML) demodulation, cooperative maximal ratio combining (C-MRC), and log-likelihood-ratio-based transmissions in mitigating error propagation effect encountered in DF cooperative networks. In order to obtain more effective solutions and improve the system performance, we introduce hybrid anti-error propagation approaches, namely VN-MRC, VN-ML, and VN-LLR in which relay selection criterion is derived by using conditional bit error rate (BER) expressions of VN technique while data detection is performed by utilizing maximal ratio combining (MRC), ML detection, C-MRC and LLR transmission methods. The performance analyses and the numerical results for cascaded Nakagami-m channels have shown that VN-LLR approach provides significant performance improvement with respect to the other considered techniques in DF cooperative vehicular systems with relay selection.

Fault-tolerant holonomic quantum computation in surface codes

We show that universal holonomic quantum computation (HQC) can be achieved fault-tolerantly by adiabatically deforming the gapped stabilizer Hamiltonian of the surface code, where quantum information is encoded in the degenerate ground space of the system Hamiltonian. We explicitly propose procedures to perform each logical operation, including logical state initialization, logical state measurement, logical CNOT, state injection and distillation,etc. In particular, adiabatic braiding of different types of holes on the surface leads to a topologically protected, non-Abelian geometric logical CNOT. Throughout the computation, quantum information is protected from both small perturbations and low weight thermal excitations by a constant energy gap, and is independent of the system size. Also the Hamiltonian terms have weight at most four during the whole process. The effect of thermal error propagation is considered during the adiabatic code deformation. With the help of active error correction, this scheme is fault-tolerant, in the sense that the computation time can be arbitrarily long for large enough lattice size. It is shown that the frequency of error correction and the physical resources needed can be greatly reduced by the constant energy gap.

Widely‐linear minimum‐mean‐squared error multiple‐candidate successive interference cancellation for multiple access interference and jamming suppression in direct‐sequence code‐division multiple‐access systems

In this paper, the authors propose a widely-linear (WL) receiver structure for multiple access interference (MAI) and jamming signal (JS) suppression in direct-sequence code-division multiple-access systems. A vector space projection (VSP) scheme is also considered to cancel the JS before detecting the desired signals. They develop a novel multiple-candidate successive interference cancellation (MC-SIC) scheme which processes two consecutive user symbols at one time to process the unreliable estimates and a number of selected points serve as the feedback candidates for interference cancellation, which is effective for alleviating the effect of error propagation in the successive interference cancellation (SIC) algorithm. WL signal processing is then used to enhance the performance of the receiver in non-circular modulation scheme. By bringing together the techniques mentioned above, a novel interference suppression scheme is proposed which combines the WL MC-SIC minimum-mean-squared error (MMSE) algorithm with the VSP scheme to suppress MAI and JS simultaneously. Simulations for binary phase shift keying modulation scenarios show that the proposed structure achieves a better MAI suppression performance compared with previously reported SIC MMSE receivers at lower complexity and a superior JS suppression performance.

Effect of Error Propagation in Stable Isotope Tracer Studies: An Approach for Estimating Impact on Apparent Biochemical Flux.

Stable isotope tracers are widely used to quantify metabolic rates, and yet a limited number of studies have considered the impact of analytical error on estimates of flux. For example, when estimating the contribution of de novo lipogenesis, one typically measures a minimum of four isotope ratios, i.e., the precursor and product labeling pre- and posttracer administration. This seemingly simple problem has 1 correct solution and 80 erroneous outcomes. In this report, we outline a methodology for evaluating the effect of error propagation on apparent physiological endpoints. We demonstrate examples of how to evaluate the influence of analytical error in case studies concerning lipid and protein synthesis; we have focused on (2)H2O as a tracer and contrast different mass spectrometry platforms including GC-quadrupole-MS, GC-pyrolysis-IRMS, LC-quadrupole-MS, and high-resolution FT-ICR-MS. The method outlined herein can be used to determine how to minimize variations in the apparent biology by altering the dose and/or the type of tracer. Likewise, one can facilitate biological studies by estimating the reduction in the noise of an outcome that is expected for a given increase in the number of replicate injections.

АНАЛИЗ ПОМЕХОУСТОЙЧИВОСТИ НЕРАВНОМЕРНЫХ КОДОВ, ПРИМЕНЯЕМЫХ ДЛЯ ПЕРЕДАЧИ ИНФОРМАЦИИ ПО КАНАЛУ СВЯЗИ

The article meets the challenge of the synchronization detection in the code sequence of uneven codes, lost in the result of impact of errors in the communication channel when transmitting compressed messages. For this purpose, basing on statistical properties of the messages and digital communication channel source, the authors got the observation likelihood functions in the presence and in the absence of synchronization. In this situation, the frequencies of occurrence of volume-defined alphabetic letters in the decoded sequence of characters can be used as the observations. As a primary distribution, the authors used a polynomial distribution, which characterizes the frequencies of occurrence of alphabetic letters in the volume-defined selection depending on their probabilities. The peculiarity of this approach for the synchronization detection is the use of polynomial distribution for description of the function of synchronization unavailability likelihood on the basis of the theory of complex hypotheses recognition with a uniform averaging. In the result of such approach, the authors obtained the likelihood ratio depending on the probabilities of alphabetic letters occurrence using which it is possible to make the conclusion about the presence or absence of synchronization. The algorithm for synchronization detection in event of non-uniform encoding was developed on the base of the sequential analysis procedure. The value of average Bayes risk presented in the form of probability of synchronization detection error was selected to be an indicator for the algorithm effectiveness evaluation. The analysis of noise stability of uneven codes shows that the application of modern multimedia technologies in communication networks increases the amount of transmitted information and used alphabet of messages that leads to the loss of synchronization and the effect of error propagation. It causes partial or total loss of data. The developed algorithm will allow recovering of the compressed messages that were distorted during their transmission via communication channel.

The blind decision feedback equalizer with the entropic: Leaky decorrelation algorithm

This paper presents the blind decision feedback equalizer (DFE) which transforms its soft feedback filter (SFBF) from the linear decor relator of received signal to the nonlinear soft feedback equalizer, and vice reversa, in order to eliminate the error propagation effects. Aiming to increase SFBF robustness in relation to the complexity of 64-QAM signal, the entropic stochastic gradient algorithm is enhanced by coefficient leaky term which restricts the overgrowth of the decorrelator coefficients in the ambient of severe inter symbol interference channels. By introducing coefficient leaky, the undesirable effects of the all-pole linear decorrelation are compensated. The achievements of the received signal decorrelation with the entropic-leaky algorithm are verified by the Monte Carlo simulations.

Robust Adaptive Intra Refresh for Multiview Video

Transmission error propagation in wireless multimedia communication systems has become a recurring problem. This persistent problem has led to grave consequences on the visual quality of the decoded video. It is against this backdrop that, we present an adaptive intra refresh (AIR) error -resilient coding tool to mitigate the effect of transmission error propagation in 3D video communications. This work utilizes periodic insertion of intra macroblocks in badly error -infected frames temporally as well as related frames in the multi view video scheme. Our objective is to maxim ize the transmission efficiency while ensuring the transmission robustness of the coded bitstream. The selection of periodic macroblocks is based on areas with high motion above a pre-set threshold. The coding modes of the macroblocks are based on the distortion expectation due to transmission errors. Extensive simulation results show significant improvement in both objective and subjective video quality at different intra refresh rates.

Global linking of cell tracks using the Viterbi algorithm.

Automated tracking of living cells in microscopy image sequences is an important and challenging problem. With this application in mind, we propose a global track linking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. The algorithm adds tracks to the image sequence one at a time, in a way which uses information from the complete image sequence in every linking decision. This is achieved by finding the tracks which give the largest possible increases to a probabilistically motivated scoring function, using the Viterbi algorithm. We also present a novel way to alter previously created tracks when new tracks are created, thus mitigating the effects of error propagation. The algorithm can handle mitosis, apoptosis, and migration in and out of the imaged area, and can also deal with false positives, missed detections, and clusters of jointly segmented cells. The algorithm performance is demonstrated on two challenging datasets acquired using bright-field microscopy, but in principle, the algorithm can be used with any cell type and any imaging technique, presuming there is a suitable segmentation algorithm.