Construction of Certain Cyclic Distance-Preserving Codes Having Linear-Algebraic Characteristics

An ordered list of binary words of length n is called a distance-preserving m, n-code, if the list distance between two words is equal to their Hamming distance, for distances up to m. A technique for constructing cyclic m, n-codes is presented, based on the standard Gray code and on some simple tools from linear algebra.     

Hyperon beta-decay and axial charges of the lambda in view of strongly distorted baryon wave-functions

Within the collective coordinate approach to chiral soliton models we suggest that breaking of SU(3) flavor symmetry mainly resides in the baryon wave-functions while the charge operators maintain a symmetric structure. Sizable symmetry breaking in the wave-functions is required to reproduce the observed spacing in the spectrum of the  baryons. The matrix elements of the flavor symmetric charge operators nevertheless yield g_A/g_V ratios for hyperon beta-decay which agree with the empirical data approximately as well as the successful F&D parameterization of the Cabibbo scheme. Demanding the strangeness component in the nucleon to vanish in the two flavor limit of the model, determines the structure of the singlet axial charge operator and yields the various quark flavor components of the axial charge of the Λ-hyperon. The suggested picture gains support from calculations in a realistic model using pion and vector meson degrees of freedom to build up the soliton.     

(Non-)anomalous D-brane and O-plane couplings: the normal bundle

The direct string computation of anomalous D-brane and orientifold plane couplings is extended to include the curvature of the normal bundle. The normalization of these terms is fixed unambiguously. New, non-anomalous gravitational couplings are found.     

Experimentally available kinetic codes as a tool for promising data extraction in thermal analysis

By the study of 3000 kinetic runs for all homogeneous two-step models under variation of activation and signal parameters, it has been stated that the generated Mechanistic Concentration Code (=MCC) is the best vehicle for data extraction in Thermal Analysis. It summarises the rate-controlling steps and their molecularities, independently of their activation data and (to 80–90%) of their method-specific signal parameters. Hence, an optimum evaluation needs the internal (best-fitted) reference step, the initial concentration of a reference reactant, and equal weight of theoretical and experimental results, reached using the same algorithms. Thus, the MCC of any series measured in general allows for a reliable model determination via the distribution into all two-step models, using the tools of probability and decision theory. A transfer of the strategy to heterogeneous reactions is discussed.

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Zusammenfassung Durch die Untersuchung von über 3000 kinetischen Abläufen für alle homogenkinetischen Zweistufen-Modelle wurde festgestellt, da\ der Mechanistische Konzentrations-Code (= MCC) ein optimaler Datenträger in der Thermischen Analyse ist: Er beschreibt die geschwindigkeitsbestimmenden Schritte und ihre Molekularität, unab- hängig von deren Aktivierungsdaten und, zu 80–90%, von ihren methodenspezifischen Signalparametern. Ein optimales Auswerteverfahren benötigt einen internen (optimal angepa\ten) Referenzschritt, die Startkonzentration eines Referenz-Reaktanten und Gleichberechtigung theoretischer und experimenteller Befunde, erreicht, durch Verwendung derselben Algorithmen. Allgemein ermöglicht der MCC aus einer Reihe von Experimenten dann eine Modellbestimmung über eine Verteilung, die durch entscheidungstheoretische Kriterien die Wahrscheinlichkeiten aller Zweistufenmodelle auflistet.Eine übertragung des Verfahrens auf heterogene Prozesse wird diskutiert.

     

DIR-Net: Deep Residual Polar Decoding Network Based on Information Refinement

Polar codes are closer to the Shannon limit with lower complexity in coding and decoding. As traditional decoding techniques suffer from high latency and low throughput, with the development of deep learning technology, some deep learning-based decoding methods have been proposed to solve these problems. Usually, the deep neural network is treated as a black box and learns to map the polar codes with noise to the original information code directly. In fact, it is difficult for the network to distinguish between valid and interfering information, which leads to limited BER performance. In this paper, a deep residual network based on information refinement (DIR-NET) is proposed for decoding polar-coded short packets. The proposed method works to fully distinguish the effective and interference information in the codewords, thus obtaining a lower bit error rate. To achieve this goal, we design a two-stage decoding network, including a denoising subnetwork and decoding subnetwork. This structure can further improve the accuracy of the decoding method. Furthermore, we construct the whole network solely on the basis of the attention mechanism. It has a stronger information extraction ability than the traditional neural network structure. Benefiting from cascaded attention modules, information can be filtered and refined step-by-step, thus obtaining a low bit error rate. The simulation results show that DIR-Net outperforms existing decoding methods in terms of BER performance under both AWGN channels and flat fading channels.     

Statistical Degree Distribution Design for Using Fountain Codes to Control the Peak-To-Average Power Ratio in an OFDM System

Utilizing fountain codes to control the peak-to-average power ratio (PAPR) is a classic scheme in Orthogonal Frequency Division Multiplexing (OFDM) wireless communication systems. However, because the robust soliton distribution (RSD) produces large-degree values, the decoding performance is severely reduced. In this paper, we design statistical degree distribution (SD) under a scenario that utilizes fountain codes to control the PAPR. The probability of the PAPR produced is combined with RSD to design PRSD, which enhances the smaller degree value produced. Subsequently, a particle swarm optimization (PSO) algorithm is used to search the optimal degree value between the binary exponential distribution (BED) and PRSD distribution according to the minimum average degree principle. Simulation results demonstrate that the proposed method outperforms other relevant degree distributions in the same controlled PAPR threshold, and the average degree value and decoding efficiency are remarkably improved.     

Fortran codes for the correlation functions of hard sphere fluids

Our Fortran codes for hard sphere fluids and their mixtures for the correlation functions that arise from the Percus–Yevick theory and the Verlet–Weis semi-empirical correction have proven useful during a period of nearly four decades and continue to be useful. In order to make these codes even more widely available, a brief summary is presented here and listings of these codes are given in the electronically accessible Supplementary Material to this paper.     

Sliding-window dynamic frameproof codes

A sliding-window dynamic frameproof code is a scheme for discouraging the piracy of digital broadcasts through the use of digital fingerprinting. In this paper, we formally define sliding-window dynamic frameproof codes and provide optimal constructions for a certain class of these schemes. We also discuss bounds on the number of users such schemes can support.      

Asymptotically good quasi-cyclic codes of fractional index

Generalizing the quasi-cyclic codes of index $1\frac{1}{3}$ introduced by Fan et al., we study a more general class of quasi-cyclic codes of fractional index generated by pairs of polynomials. The parity check polynomial and encoder of these codes are obtained. The asymptotic behaviours of the rates and relative distances of this class of codes are studied by using a probabilistic method. We prove that, for any positive real number $\delta$ such that the asymptotic GV-bound at $\frac{k+l}{2}\delta$ is greater than $\frac{1}{2}$, the relative distance of the code is convergent to $\delta$, while the rate is convergent to $\frac{1}{k+l}$. As a result, quasi-cyclic codes of fractional index are asymptotically good.