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lssue 12, 2025
Editors-in-Chief
Yunhe Pan, Aiguo Fei
Advisor Xicheng Lu
ISSN 3069-8928
CN 33-1439/TP
IF (2024 JCR) 2.9
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Volume 27 Issue 1，2026
常规文章
Regular Papers
Miniaturized bandpass filter with a wide upper stopband using isomeric resonators in a cavity Enhanced Publication AI Introduction
“Researchers have developed a compact third-order bandpass filter based on heterogeneous resonators within a cavity. By introducing tuning posts and half-wavelength resonant slots, the filter achieves significant size reduction and enhanced performance. This innovation offers a solution for miniaturizing microwave devices while maintaining high performance.”Abstract：本文提出一种基于腔体内异构谐振器的紧凑型三阶带通滤波器。该滤波器由两个脊波导谐振器以及位于其间的半波长谐振缝隙构成。基于脊波导谐振器前两阶模态（TE101与TE102模）的电场分布特性，在脊中心电场集中的位置引入调谐柱（Tup）。由于TE101模在该位置电场较强，TE102模电场较弱，因此调谐柱的引入可显著降低基模TE101的谐振频率，而对一阶谐波TE102的影响较小，从而同时实现结构小型化与宽无杂散响应范围。此外，在两个脊波导谐振器之间引入半波长谐振缝隙（HWRS）谐振器，实现三阶滤波器结构，在缩短滤波器整体长度的同时，通过交叉耦合在上阻带引入传输零点。此外，HWRS谐振器的厚度为交叉耦合提供了额外的调控路径，使传输零点能够在一定范围内实现精确调节。基于上述设计方法，实现了一种结构紧凑、性能优良的直列型带通滤波器。与传统脊波导滤波器相比，该滤波器尺寸缩小约90%，同时获得更宽的上阻带抑制范围。Keywords：紧凑型滤波器;宽上阻带;脊波导谐振器;半波长谐振缝隙;调谐柱;传输零点12|1|0Updated：2026-02-06Regular Papers
Key technologies of vertical take-off and landing infrastructure for urban air mobility: a comprehensive review Enhanced Publication AI Introduction
“Urban air mobility (UAM) is gaining attention for its efficiency and low carbon footprint. However, the key technologies for low-altitude VTOL infrastructure are still in their early stages. To address this, experts have systematically reviewed progress and trends, proposing a conceptual design for a public multioperator VTOL site to support sustainable low-altitude economy growth.”Abstract：As the frontier of multidimensional transportation systems, urban air mobility (UAM) is receiving increasing attention from international organizations, governments, and stakeholders in industry and academia owing to its high efficiency, low carbon footprint, and operational flexibility. Vertical take-off and landing (VTOL) infrastructure is the core facility that enables UAM and is therefore essential for its safe, efficient, and large-scale commercial implementation. However, the key technologies for establishing low-altitude VTOL infrastructure are still nascent, and government, industry, and academia have yet to harmonize the corresponding construction, management, and operation standards. To address this gap, we herein systematically review the related progress and trends, comprehensively surveying the key technologies of establishing VTOL infrastructure serving unmanned aerial vehicles (UAVs) and electric VTOL aircraft from three complementary perspectives of ground-side, airspace-side, and communication, navigation, surveillance, and information services. In the light of future UAM operations characterized by diverse vehicle types and dense air traffic, we propose a conceptual design for a public multioperator VTOL site to provide constructive insights into the sustainable growth of the low-altitude economy.Keywords：Urban air mobility (UAM);Vertical take-off and landing (VTOL) infrastructures;Low-altitude operations;Communication, navigation, surveillance, and information (CNSI)11|2|0Updated：2026-02-06Regular Papers
Energy dynamics and circuit implementation for a neuron with a memcapacitive membrane Enhanced Publication AI Introduction
“Researchers have made significant strides in modeling neural circuits. They developed a dimensionless neuron model that simulates neuronal behavior under various conditions. By incorporating a memcapacitor, the model accounts for membrane deformation effects, enhancing its accuracy. The study also proposes an adaptive control strategy to regulate neuronal activity, validated through an analog equivalent circuit.”Abstract：The output voltages for the capacitive elements of a neural circuit model can be mapped into dimensionless capacitive variables, which present firing patterns similar to the membrane potentials detected in biological neurons. The inclusion of a memcapacitor also enables consideration of membrane deformation effects, enhancing the model’s capacity to simulate neuronal behavior across varying physiological and environmental conditions. In this study, a capacitor and a memcapacitor are connected through a linear resistor in parallel with other electric components in different branch circuits composed of an inductor and a nonlinear resistor. The electrical activities in a neuron with a double-layer membrane and two capacitive variables are discussed in detail after converting the nonlinear equations for the neural circuit into a theoretical neuron model. A dimensionless neuron model and its corresponding energy function are derived. The field energy function for the neural circuit is converted into an equivalent Hamilton energy function and further validated via the Helmholtz theorem. Furthermore, the average value of energy serves as an indicator for predicting stochastic resonance, as supported by analyzing the distribution of the coefficient of variation. The neuronal firing patterns are shown to be energy-dependent. An adaptive control strategy is proposed to regulate mode transitions in electrical activities of the neuron. An analog equivalent circuit is constructed to experimentally verify the numerical results, thereby supporting the reliability of the proposed neuron model.Keywords：Neural circuit;Neuron model;Hamilton energy;Memcapacitor;Coherence resonance4|1|0Updated：2026-02-06Regular Papers
A review of UAV positioning in LAIN: toward a 5G-core “space-air-ground” integrated and cooperative architecture Enhanced Publication AI Introduction
“The low-altitude economy's rapid growth is fueling demand for precise positioning technologies. A new review examines core positioning methods within the low-altitude intelligent network (LAIN) framework. It assesses mainstream systems like GNSS and proposes a “space-air-ground” integrated architecture centered on GNSS and 5G. This architecture enhances positioning robustness and reduces costs, offering a novel perspective for LAIN development.”Abstract：The rapid expansion of the low-altitude economy is driving strong demand for highly accurate and reliable positioning technologies to support diverse aerial operations. This review examines core positioning methodologies within the low-altitude intelligent network (LAIN) framework, beginning with an analysis of positioning requirements and performance metrics for low-altitude flight scenarios. It systematically assesses the principles, strengths, and limitations of mainstream positioning systems, including Global Navigation Satellite Systems (GNSS), terrestrial wireless positioning, and autonomous navigation, and it surveys prevalent integrated and cooperative positioning schemes. Our analysis demonstrates that standalone positioning technologies are inadequate in complex low-altitude settings, underscoring the pivotal role of multi-source fusion and unmanned aerial vehicle (UAV) swarm cooperative positioning as future trends. To address infrastructure gaps and high deployment costs in current LAIN systems, we propose a “space-air-ground” integrated and cooperative positioning architecture centered on GNSS and the 5th generation mobile communication technology (5G). The ground layer integrates 5G and GNSS for wide-area enhanced positioning. The aerial layer uses 5G aircraft-to-everything (A2X) and sidelink (SL) communications to build self-organizing networks for cooperative UAV localization. The space layer leverages low Earth orbit (LEO) satellites to overcome coverage limitations in communication and positioning. This hierarchical architecture reduces deployment costs through infrastructure reuse and enables deep integration of communication and navigation capabilities. By supporting collaborative enhancement across all three domains, the framework improves positioning robustness and delivers cost-effective, ubiquitous, and highly reliable positioning services. Finally, we outline promising research directions. This review aims to provide a systematic reference and a novel architectural perspective for the ongoing development of LAIN.Keywords：Low-altitude intelligent network (LAIN);Unmanned aerial vehicle (UAV);Integrated positioning;Integrated communication and navigation;Space-air-ground collaboration3|0|0Updated：2026-02-06Regular Papers
TP-ViT: truncated uniform-log2 quantizer and progressive bit-decline reconstruction for vision Transformer quantization AI Introduction
“Vision Transformers (ViTs) have made significant strides in AI-based computer vision applications. However, deploying ViTs on edge devices is challenging due to their high computational and memory demands. To tackle this, researchers have developed the TP-ViT framework, which includes a truncated uniform-log2 quantizer and a bit-decline optimization strategy. These innovations significantly reduce quantization errors and maintain model performance, even under extreme low-bit conditions. Experiments show TP-ViT outperforms state-of-the-art methods, especially in 3-bit quantization, achieving a 6.18 percentage points improvement in top-1 accuracy for ViT-small. This advancement paves the way for more efficient ViT deployment on edge hardware.”Abstract：Vision Transformers (ViTs) have achieved remarkable success across various artificial intelligence-based computer vision applications. However, their demanding computational and memory requirements pose significant challenges for deployment on resource-constrained edge devices. Although post-training quantization (PTQ) provides a promising solution by reducing model precision with minimal calibration data, aggressive low-bit quantization typically leads to substantial performance degradation. To address this challenge, we present the truncated uniform-log2 quantizer and progressive bit-decline reconstruction method for vision Transformer quantization (TP-ViT). It is an innovative PTQ framework specifically designed for ViTs, featuring two key technical contributions: (1) truncated uniform-log2 quantizer, a novel quantization approach which effectively handles outlier values in post-Softmax activations, significantly reducing quantization errors; (2) bit-decline optimization strategy, which employs transition weights to gradually reduce bit precision while maintaining model performance under extreme quantization conditions. Comprehensive experiments on image classification, object detection, and instance segmentation tasks demonstrate TP-ViT’s superior performance compared to state-of-the-art PTQ methods, particularly in challenging 3-bit quantization scenarios. Our framework achieves a notable 6.18 percentage points improvement in top-1 accuracy for ViT-small under 3-bit quantization. These results validate TP-ViT’s robustness and general applicability, paving the way for more efficient deployment of ViT models in computer vision applications on edge hardware.Keywords：Vision Transformers;Post-training quantization;Block reconstruction;Image classification;Object detection;Instance segmentation3|2|0Updated：2026-02-06
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0 1 Hybrid-augmented intelligence: collaboration and cognition
0 4 Applications of artificial intelligence in intelligent manufacturing: a review*
0 5 Challenges and opportunities: from big data to knowledge in AI 2.0
0 6 Current trends in the development of intelligent unmanned autonomous systems
0 7 Recent advances in efficient computation of deep convolutional neural networks
0 8 Terahertz time-domain spectroscopy and micro-cavity components for probing samples: a review
0 9 Cross-media analysis and reasoning: advances and directions
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P1 Speech by Academician Baoyan Duan
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P2 Speech by Professor Min Sheng, Xidian University
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P3 Speech by Professor Yunsong Li, Xidian University
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