基于核估计的滤波补偿法

为了解决Kalman滤波算法进行动态定位时,模型中存在的系统误差使得动态定位结果产生偏差的问题,采用基于核估计的滤波补偿法,在移动的窗口内,利用核估计拟合模型系统误差,修正相应的观测向量和状态预测向量的协方差矩阵估值,以消除系统误差对滤波的影响,推导了利用核估计拟合系统误差的公式。通过一个模拟算例证明了改算法的有效性,而且在滤波过程中不需要对系统误差做任何假设,对开窗窗口的宽度也不敏感。     

Linearity and classification of ZpZp2-linear generalized Hadamard codes

The ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-additive codes are subgroups of ${\mathbb{Z}}_p^{{\alpha }_1}\times {\mathbb{Z}}_{p^2}^{{\alpha }_2}$, and can be seen as linear codes over ${\mathbb{Z}}_p$ when ${\alpha }_2=0$, ${\mathbb{Z}}_{p^2}$-additive codes when ${\alpha }_1=0$, or ${\mathbb{Z}}_2{\mathbb{Z}}_4$-additive codes when $p=2$. A ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-linear generalized Hadamard (GH) code is a GH code over ${\mathbb{Z}}_p$ which is the Gray map image of a ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-additive code. Recursive constructions of ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-additive GH codes of type $({\alpha }_1,{\alpha }_2;t_1,t_2)$ with $t_1,t_2\ge 1$ are known. In this paper, we generalize some known results for ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-linear GH codes with $p=2$ to any $p\ge 3$ prime when ${\alpha }_1\ne 0$, and then we compare them with the ones obtained when ${\alpha }_1=0$. First, we show for which types the corresponding ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-linear GH codes are nonlinear over ${\mathbb{Z}}_p$. Then, for these codes, we compute the kernel and its dimension, which allow us to classify them completely. Moreover, by computing the rank of some of these codes, we show that, unlike ${\mathbb{Z}}_4$-linear Hadamard codes, the ${\mathbb{Z}}_{p^2}$-linear GH codes are not included in the family of ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-linear GH codes with ${\alpha }_1\ne 0$ when $p\ge 3$ prime. Indeed, there are some families with infinite nonlinear ${\mathbb{Z}}_p{\mathbb{Z}}_{p^2}$-linear GH codes, where the codes are not equivalent to any ${\mathbb{Z}}_{p^s}$-linear GH code with $s\ge 2$.     

Recent studies on advance spectroscopic techniques for the identification of microorganisms: A review

The continuous development of resistance to antibiotic drugs by microorganisms causes high mortality and morbidity. Pathogens with distinct features and biochemical abilities make them destructive to human health. Therefore, early identification of the pathogen is of substantial importance for quick ailments and healthcare outcomes. Several phenotype methods are used for the identification and resistance determination but most of the conventional procedures are time-consuming, costly, and give qualitative results. Recently, great focus has been made on the utilization of advanced techniques for microbial identification. This review is focused on the research studies performed in the last five years for the identification of microorganisms particularly, bacteria using advanced spectroscopic techniques including mass spectrometry (MS), infrared (IR) spectroscopy, Raman spectroscopy (RS), and nuclear magnetic resonance (NMR) spectroscopy. Among all the techniques, MS techniques, particularly MALDI-TOF/MS have been widely utilized for microbial identification. A total of 44 bacteria i.e., 6 Staphylococcus spp., 3 Enterococcus spp., 6 Bacillus spp., 4 Streptococcus spp., 6 Salmonella spp., and one from each genus including Escherichia, Acinetobacter, Pseudomonas, Proteus, Clostridioides, Candida, Brucella, Burkholderia, Francisella, Yersinia, Moraxella, Vibrio, Shigella, Serratia, Citrobacter, and Haemophilus (spp.) were discussed in the review for their identification using the above-mentioned techniques. Among all the identified microorganisms, 21% of studies have been conducted for the identification of E. coli, 14% for S. aureus followed by 37% for other microorganisms.