Weight distributions of a class of cyclic codes with arbitrary number of nonzeros in quadratic case

Cyclic codes are an important class of linear codes, whose weight distribution have been extensively studied. So far, most of previous results obtained were for cyclic codes with no more than three nonzeros. Recently, the authors of [37] constructed a class of cyclic codes with arbitrary number of nonzeros, and computed the weight distribution for several cases. In this paper, we determine the weight distribution for a new family of such codes. This is achieved by introducing certain new methods, such as the theory of Jacobi sums over finite fields and subtle treatment of some complicated combinatorial identities.     

Uniform stable conformal convolutional perfectly matched layer for enlarged cell technique conformal finite-difference time-domain method

Based on conformal construction of physical model in a three-dimensional Cartesian grid,an integral-based conformal convolutional perfectly matched layer(CPML) is given for solving the truncation problem of the open port when the enlarged cell technique conformal finite-difference time-domain(ECT-CFDTD) method is used to simulate the wave propagation inside a perfect electric conductor(PEC) waveguide.The algorithm has the same numerical stability as the ECT-CFDTD method.For the long-time propagation problems of an evanescent wave in a waveguide,several numerical simulations are performed to analyze the reflection error by sweeping the constitutive parameters of the integral-based conformal CPML.Our numerical results show that the integral-based conformal CPML can be used to efficiently truncate the open port of the waveguide.     

Combining convolutional neural networks and in‐line near‐infrared spectroscopy for real‐time monitoring of the chromatographic elution process in commercial production of notoginseng total saponins

The chromatographic elution process is a key step in the production of notoginseng total saponins. Due to quality variability of loading samples and resin capacity decreasing over cycle time, saponins, especially the five main saponins of notoginseng total saponins, need to be monitored in real time during the elution process. In this study, convolutional neural networks, one of the most popular deep learning methods, were used to develop quantitative calibration models based on in‐line near‐infrared spectroscopy for notoginsenoside R₁, ginsenosides Rg₁, Re, Rb₁ and Rd, and their sum concentration, with root mean square error of prediction values of 0.87, 2.76, 0.60, 1.57, 0.28, and 4.99 mg/mL, respectively. Partial least squares calibration models were also developed for model performance comparison. Results show predicted concentration profiles outputted by both the convolutional neural network models and partial least squares models show agreements with the real trends defined by reference measurements, and can be used for elution process monitoring and endpoint determination. To the best of our knowledge, this is the first reported case study of combining convolutional neural networks and in‐line near‐infrared spectroscopy for monitoring of the chromatographic elution process in commercial production of botanical drug products.     

中短波信道中基于LDPC码的迭代解调译码方案

针对数字调幅广播系统,首次提出了基于迭代解调的低密度奇偶校验(LDPC)编码的比特交织编码调制(BICM)方案.首先研究了LDPC码的映射方式,然后基于复杂度分析,考察了LDPC码、Turbo码及国际标准中码率匹配的删除卷积码(RCPC)方案在中、短波广播信道中的性能.研究结果可为我国调幅波段的数字广播系统提供参考.     

一种新的OVSF码快速生成分配算法研究

本文利用复制方法提出一种新的OVSF码复制生成算法,并在此基础上,研究了非可重排和可重排两种情况下的OVSF码快速分配问题.利用复制生成的OVSF码字具有明显的异前置性特点,从而可以提高码字分配效率和减小硬件实现复杂度和降低呼叫阻塞率.     

Turbo码的一种并行译码方案及相应的并行结构交织器研究

Turbo码基于MAP算法译码的递推计算所引入高的译码延迟限制了Turbo码在高速率数据传输中的应用。为了解决这个问题,该文提供了一种降低译码延迟的并行译码方法。并行处理方案的实现必须通过适当的交织以避免两个译码器对外信息读写的数据冲突。该文在分析了任意无冲突交织方式可能性的存在之后,给出了设计任意地适用于并行处理方案的S随机交织器的方法。仿真验证了并行译码方案的误比特性能。     

三类混沌二相码性能分析

为产生伪随机编码雷达波形,提高雷达低截获概率（LIP）和电子反干扰（ECCM）性能。针对logistic、full logistic、Kent三类最具代表性的映射所产生的混沌序列,在大量仿真基础上,对由此三类混沌序列获得的二相码相关性、平衡性及游程性等性能进行了比较分析,并给出了相应的仿真结果。研究表明三类混沌序列,都具有较好的伪随机特性,由此均可获得产生雷达波形的理性混沌二相码,Kent序列和full logistic序列的综合性能较好。