基于贝叶斯压缩感知的子空间拟合离格DOA估计

针对传统的基于稀疏贝叶斯学习（Sparse Bayesian Learning,SBL）的波达方向估计算法对噪声鲁棒性不高的问题,提出了一种基于SBL的子空间拟合离格波达方向(Direction of Arrival,DOA)估计方法。首先对接收数据的协方差矩阵进行特征分解,获得信号的加权子空间,构造等价信号的稀疏表示模型并利用贝叶斯学习算法进行参数求解。同时对于网格划分带来的建模误差问题,采用了离格贝叶斯推导（Sparse Bayesian Inference,SBI）算法进行求解,利用期望最大化算法迭代更新相应的参数。仿真结果表明,相对于传统的DOA方法,该方法具有更好的估计精度。     

基于感知域测量值的自适应压缩采样方法

现有的自适应采样方法需要在采集端获得原始信号,这在实际的蒸发波导相关气象要素压缩感知过程中不易实现。针对这一问题,提出了一种以测量值数据特征为依据的采样率自适应设定方法。该方法以能量表征各信号块的重要性,以观测值能量近似估计原信号块能量,根据感知域中测量值的能量变化自适应地为各块设定采样数目。理论分析和实验表明,该方法的重构性能优于传统自适应方法,相同采样率下可获得更高的重构信噪比。     

基于竞争双深度Q网络的频谱感知和接入

认知用户通过频谱感知和接入过程识别频谱状态并占用空闲频谱,可有效利用频谱资源。针对频谱感知中存在感知错误和频谱接入中存在用户碰撞的问题,首先建立多用户多信道模型,设计频谱感知和频谱接入过程;然后通过结合双深度Q网络和竞争Q网络,设计竞争双深度Q网络,解决过估计问题的同时优化网络结构;最后通过智能体与所设计模型中状态、观测、回报和策略的交互,完成使用竞争双深度Q网络解决频谱感知和接入问题的一体化研究。仿真结果表明,相比于已有深度强化学习方法,使用竞争双深度Q网络得到的数值结果更稳定且感知正确率和信道利用率都提高了4%。     

Soft Robotic-Adapted Multimodal Sensors Derived from Entirely Intrinsic Self-Healing and Stretchable Cross-Linked Networks

Flexible sensing technologies that play a pivotal role in endowing robots with detection capabilities and monitoring their motions are impulsively desired for intelligent robotics systems. However, integrating and constructing reliable and sustainable flexible sensors with multifunctionality for robots remains an everlasting challenge. Herein, an entirely intrinsic self-healing, stretchable, and attachable multimodal sensor is developed that can be conformally integrated with soft robots to identify diverse signals. The dynamic bonds cross-linked networks including the insulating polymer and conductive hydrogel with good comprehensive performances are designed to fabricate the sensor with prolonged lifespan and improved reliability. Benefiting from the self-adhesiveness of the hydrogel, strong interfacial bonding can be formed on various surfaces, which promotes the conformable integration of the sensor with robots. Due to the ionic transportation mechanism, the sensor can detect strain and temperature based on piezoresistive and thermoresistive effect, respectively. Moreover, the sensor can work in triboelectric mode to achieve self-powered sensing. Various information can be identified from the electrical signals generated by the sensor, including hand gestures, soft robot crawling motions, a message of code, the temperature of objects, and the type of materials, holding great promise in the fields of environmental detection, wearable devices, human-machine interfacing, and robotics.     

Biomimetic Aerogel for Moisture-Induced Energy Harvesting and Self-Powered Electronic Skin

Moisture–electric generator (MEG)-based blue energy is widely studied. There is still a significant challenge in improving the power of the MEGs system and expanding its application in self-powered electronic skin. Inspired by the structure of ferns, a biomimetic moisture–electric aerogel is designed to collect energy. Polyvinyl alcohol dendritic colloids act as “roots” and “stems” to provide support and channels to transport water molecules. Meanwhile, “leaf-like” graphene oxide sheets generate electricity through direct interaction with water. Besides, based on the above biomimetic structure, this work further enhances the output performance of MEGs by increasing the specific surface area (120.4 m² g⁻¹) and introducing an ultra-high ion density gradient (from −35 to +37 mV). Meanwhile, due to the excellent water absorption, the MEGs show good salt resistance and cyclic stability. By constructing unique biomimetic structures, ultra-high ion density gradient, and regulating environmental conditions, a high-performance MEG is obtained, including ultra-high open-circuit voltage (1.9 V) and short-circuit current (82.5 µA), the industry-leading power density among MEGs with continuous output is reported in the literature (22.55 µW cm⁻²). Besides, the MEGs can accurately respond to environmental and pressure changes, showing its application potential in self-powered electronic skin.     

A Soft,Fast and Versatile Electrohydraulic Gripper with Capacitive Object Size Detection

Soft robotic grippers achieve increased versatility and reduced complexity through intelligence embodied in their flexible and conformal structures. The most widely used soft grippers are pneumatically driven; they are simple and effective but require bulky air compressors that limit their application space and external sensors or computationally expensive vision systems for pick verification. In this study, a multi-material architecture for self-sensing electrohydraulic bending actuators is presented that enables a new class of highly versatile and reconfigurable soft grippers that are electrically driven and feature capacitive pick verification and object size detection. These electrohydraulic grippers are fast (step input results in finger closure in 50 ms), draw low power (6.5 mW per finger to hold grasp), and can pick a wide variety of objects with simple binary electrical control. Integrated high-voltage driving electronics are presented that greatly increase the application space of the grippers and make them readily compatible with commercially available robotic arms.     

Petromyzontidae-Biomimetic Multimodal Microneedles-Integrated Bioelectronic Catheters for Theranostic Endoscopic Surgery

Current catheter devices in minimally invasive surgery still possess limited functional options, lacking multimodal integration of both sensing and therapy. Catheter devices usually operate outside the tissue, incapable to detect intra-tissue biochemical information for accurate localization and assessment of lesions during surgery. Inspired by the feature and functions of Petromyzontidae, here a multimodal core-shell microneedles-integrated bioelectronic catheter (MNIBC) for tissue-penetrating theranostics in endoscopic surgery is developed. The microneedle (MN) device possesses individually addressable functionality at single-MN tip resolution, enabling multiplex functions (a total of 11 functions distributed in three types of catheters) including biochemical sensing, myoelectric modulation, electroporation, and drug delivery in a submucosal environment. The MNIBC is prepared through hybrid fabrication and dimensionality reduction strategies, where the MN electrodes are functionalized with an MXene-carbon nanotube (MXene-CNT)-based electron mediator, addressing the challenge of reduced electrode sensitivity on ultra-small MN tip. The functionalities of MNIBC are demonstrated both ex vivo and in vivo on anesthetized rabbits via laparoscopy, simulated cystoscopy, and laparotomy. The MNIBC can effectively detect intra-tissue biochemical signals in the bladder, and offers localized electroporation and intra-tissue drug delivery for precise treatments of lesions. The versatile features of the MNIBC present a highly advanced platform for precise surgeries.     

Ultra-Stable and Sensitive Ultraviolet Photodetectors Based on Monocrystalline Perovskite Thin Films

The detection of ultraviolet (UV) radiation with effective performance and robust stability is essential to practical applications. Metal halide single-crystal perovskites (ABX₃) are promising next-generation materials for UV detection. The device performance of all-inorganic CsPbCl₃ photodetectors (PDs) is still limited by inner imperfection of crystals grown in solution. Here wafer-scale single-crystal CsPbCl₃ thin films are successfully grown by vapor-phase epitaxy method, and the as-constructed PDs under UV light illumination exhibit an ultralow dark current of 7.18 pA, ultrahigh ON/OFF ratio of ≈5.22 × 10⁵, competitive responsivity of 32.8 A W⁻¹, external quantum efficiency of 10867% and specific detectivity of 4.22 × 10¹² Jones. More importantly, they feature superb long-term stability toward moisture and oxygen within twenty-one months, good temperature tolerances at low and high temperatures. The ability of the photodetector arrays for excellent UV light imaging is further demonstrated.     

On-chip Diamond MEMS Magnetic Sensing through Multifunctionalized Magnetostrictive Thin Film

Electrically integrable, high-sensitivity, and high-reliability magnetic sensors are not yet realized at high temperatures (500 °C). In this study, an integrated on-chip single-crystal diamond (SCD) micro-electromechanical system (MEMS) magnetic transducer is demonstrated by coupling SCD with a large magnetostrictive FeGa film. The FeGa film is multifunctionalized to actuate the resonator, self-sense the external magnetic field, and electrically readout the resonance signal. The on-chip SCD MEMS transducer shows a high sensitivity of 3.2 Hz mT⁻¹ from room temperature to 500 °C and a low noise level of 9.45 nT Hz^−1/2 up to 300 °C. The minimum fluctuation of the resonance frequency is 1.9 × 10⁻⁶ at room temperature and 2.3 × 10⁻⁶ at 300 °C. An SCD MEMS resonator array with parallel electric readout is subsequently achieved, thus providing a basis for the development of magnetic image sensors. The present study facilitates the development of highly integrated on-chip MEMS resonator transducers with high performance and high thermal stability.     

面向鲁棒频谱感知的模糊K-means++算法

恶意用户通过向数据融合中心发送伪造的频谱感知数据,解决自身频谱资源短缺问题,但会极大地降低频谱感知系统的检测概率。为了解决此问题,提出了基于模糊K means++的数据融合算法。该算法首先引入模糊处理机制处理样本的数据特征值,以此来增加样本间的差异性;然后将模糊处理后的数据发送到融合中心,融合中心采用离群点挖掘的方法排除恶意用户,并对保留下来的用户进行融合,使样本向量具有鲁棒性;最后运用K means++算法对样本向量进行聚类。该算法利用轮盘法选择聚类中心,可有效抵御恶意用户的攻击,提高系统感知性能;无需知晓信号与噪声的分布等一些先验信息,也避免了繁杂的门限推导。从仿真结果可以看出,该算法对抵御恶意用户攻击具有突出的效果,有效提升了协同频谱感知系统的稳定性和鲁棒性。