Due to the importance of weighted fractional Fourier transform (WFRFT) applications, it has become an important technology in the fields of OFDM and CDMA. Although the single parameter weighted ...fractional Fourier transform (SPWFRFT) is the most widely used method at present, the multiple-parameter weighted fractional Fourier transform (MPWFRFT) has received increasing attention in order to further improve the anti-scanning performance of the system. Thus, considering the characteristics of digital communications signals with the MPWFRFT, the anti-scanning method is investigated herein. By studying the process of the SPWFRFT, we establish the influence factors and calculate the weighted coefficients. Then, the influence factor is spread, and multiple parameters are added, which allow MPWFRFT processing to be studied in-depth. Based on this research, we carry out anti-scanning research under different conditions. By studying the relationship between the parameters M and V, the optimal parameter setting rules are given. Further, the bit error rate is discussed emphatically, and the minimum scanning interval of all parameters is given. In addition, we discuss the complexity and how to easily decode the useful signals at the receiver, and then the anti-scanning performance of MPWFRFT communication systems is proved.
A direct-sequence spread-spectrum (DSSS) signal has many advantages, such as low SNR and strong anti-jamming ability; thus, it is widely used in various military and civil communication systems. ...However, hiding and high-data-rate transmission technologies have become the key factors affecting the future applications of the existing DSSS. To solve these problems, an incremental-data stealth-transmission (IDST) method is proposed, which stealthily transmits incremental data through variations in the spread spectrum function and alternation of the weighted fractional Fourier transform modulation order. The incremental data are not transmitted through a real channel but through the function relationship to achieve index transmission. Without affecting the spread spectrum gain and SNR tolerance of the original data, the proposed method greatly improves the amount of information transmitted and enhances the concealment of incremental data.
Jurassic sandstones in the Xiongcun porphyry copper–gold district, southern Lhasa subterrane, Tibet, China were analysed for petrography, major oxides and trace elements, as well as detrital zircon ...U–Pb and Hf isotopes, to infer their depositional age, provenance, intensity of source-rock palaeo-weathering and depositional tectonic setting. This new information provides important evidence to constrain the tectonic evolution of the southern Lhasa subterrane during the Late Triassic – Jurassic period. The sandstones are exposed in the lower and upper sections of the Xiongcun Formation. Their average modal abundance (Q21F11L68) classifies them as lithic arenite, which is also supported by geochemical studies. The high chemical index of alteration values (77.19–85.36, mean 79.96) and chemical index of weathering values (86.19–95.59, mean 89.98) of the sandstones imply moderate to intensive weathering of the source rock. Discrimination diagrams based on modal abundance, geochemistry and certain elemental ratios indicate that felsic and intermediate igneous rocks constitute the source rocks, probably with a magmatic arc provenance. The detrital zircon ages (161–243 Ma) and εHf(t) values (+10.5 to +16.2) further constrain the sandstone provenance as subduction-related Triassic–Jurassic felsic and intermediate igneous rocks from the southern Lhasa subterrane. A tectonic discrimination method based on geochemical data of the sandstones, as well as detrital zircon ages from sandstones, reveals that the sandstones were most likely deposited in an oceanic island-arc setting. These results support the hypothesis that the tectonic background of the southern Lhasa subterrane was an oceanic island-arc setting, rather than a continental island-arc setting, during the Late Triassic – Jurassic period.
It is critical to detect malicious code for the security of the Internet of Things (IoT). Therefore, this work proposes a malicious code detection algorithm based on the novel feature fusion-malware ...image convolutional neural network (FF-MICNN). This method combines a feature fusion algorithm with deep learning. First, the malicious code is transformed into grayscale image features by image technology, after which the opcode sequence features of the malicious code are extracted by the n-gram technique, and the global and local features are fused by feature fusion technology. The fused features are input into FF-MICNN for training, and an appropriate classifier is selected for detection. The results of experiments show that the proposed algorithm exhibits improvements in its detection speed, the comprehensiveness of features, and accuracy as compared with other algorithms. The accuracy rate of the proposed algorithm is also 0.2% better than that of a detection algorithm based on a single feature.
In this paper, a two-dimensional information transmission method based on k step-complex spread spectrum (KS-CSS) is proposed. The aim is to solve the contradiction between the bandwidth and ...processing gain of a traditional direct-sequence spread spectrum (DSSS) channel, and to achieve better system performance (such as by obtaining higher processing gain and higher bandwidth utilization). Using the multi-domain characteristics of DSSS signals, based on the time–frequency characteristics of a DSSS, the code-domain characteristics are further combined. The KS-CSS method calculates the control coefficients such as modulation order, PN code group, and conversion time. Thus, dependence mapping for additional two-dimensional data transmission is established. Then, the spread spectrum pseudo-code is mapped and processed with one-dimensional data. Theoretical analysis and simulation results show that the time–frequency domain characteristics of the KS-CSS signal are consistent with those of traditional DSSS signals. However, the information transmission rate can be increased by more than 100%, and the bit error rate of data can be significantly improved. The high-speed transmission performance and low bit error rate of the KS-CSS method can provide a theoretical basis and technical reference for high-performance spread spectrum communication.
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.
The traditional approach to ship pipeline programming often involves describing and calculating based on text files. This method tends to be error-prone and time-consuming, especially for complex ...systems with a large amount of data related to pipelines. In case of system failures, troubleshooting becomes inconvenient. Additionally, matrix calculations can lead to issues such as extreme values, and visualizing the results is challenging. To address these challenges, this paper proposes an intuitive, user-friendly, and efficient ship pipeline programming tool. The tool utilizes Microsoft's WPF (Windows Presentation Foundation) graphical interface technology and the C# programming language. A graphical interface for ship pipeline networks is constructed, allowing users to visually build the physical model of pipelines through intuitive drag-and-drop and connection operations. Furthermore, the paper adopts Excel spreadsheets as the input method for data and combines it with domain knowledge of marine engineering pipelines. This approach establishes logical models for various pipelines, valves, and other equipment on ships. The models incorporate attributes from the spreadsheet to control characteristics like maximum flow rates and flow directions. By combining graphical modules, pipeline connections, and Excel spreadsheets, the method proposed in this paper offers a more convenient way to construct pipeline network models. The resulting models closely resemble actual ship pipelines, leading to improved accuracy and efficiency in data processing and calculations.
With the continuous improvement of the application requirements of Direct Sequence Spread Spectrum (DSSS), especially the high requirements of data transmission rate, the advantages of traditional ...DSSS system are limited, so the index modulation DSSS technology appears. However, at present, there are still some key problems such as high‐order data rate, high bit error rate and high synchronisation complexity. Therefore, in view of the above bottleneck problems, the code index modulation method with multidimensional invisible data (MID‐CIM) is proposed. On the basis of deeply mining the hidden features of DSSS communication mechanism, the index order and shift order are established, and the two‐dimensional invisible data index transmission rules are established using a bit reversed and pseudo code (PN) set mapping mechanism, and then the three‐dimensional invisible data index transmission rules are established by using the cyclic displacement and pseudo code offset mechanism. The MID‐CIM method not only ensures the effective transmission of one‐dimensional data, but also uses the transmission of low‐speed one‐dimensional data to index transmit high‐speed two‐dimensional and three‐dimensional invisible data. This research can provide the technical basis for the efficient application of DSSS system, and also provide theoretical support and technical support for the new development and application of a communication system based on the spread spectrum system.
The continuously increasing number of connected smart devices has led to the emergence of a crucial fault detection challenge to the Internet of Things (IoT). In this study, we aim to identify a ...method for the effective detection of faults in IoT devices. An IoT network model is first established, and a data edge verification mechanism based on blockchain is proposed; the blockchain is used to ensure that the data cannot be tampered with, and their accuracy is verified using the edge. Finally, a data set accuracy weighted random forest based on particle swarm optimization is proposed. The simulation results demonstrate that the proposed detection algorithm is both effective and efficient.
