Robust Absolute Stability Criteria for a Class of Uncertain Lur'e Systems of Neutral Type

This paper is concerned with the problem of robust absolute stability for a class of uncertain Lur'e systems of neutral type. Some delay-dependent stability criteria are obtained and formulated in the form of linear matrix inequalities (LMIs). Neither model transformation nor bounding technique for cross terms is involved through derivation of the stability criteria. A numerical example shows the effectiveness of the criteria

Distributed filtering of networked dynamic systems with non-gaussian noises over sensor networks: A survey

summary:Sensor networks are regarded as a promising technology in the field of information perception and processing owing to the ease of deployment, cost-effectiveness, flexibility, as well as reliability. The information exchange among sensors inevitably suffers from various network-induced phenomena caused by the limited resource utilization and complex application scenarios, and thus is required to be governed by suitable resource-saving communication mechanisms. It is also noteworthy that noises in system dynamics and sensor measurements are ubiquitous and in general unknown but can be bounded, rather than follow specific Gaussian distributions as assumed in Kalman-type filtering. Particular attention of this paper is paid to a survey of recent advances in distributed filtering of networked dynamic systems with non-Gaussian noises over sensor networks. First, two types of widely employed structures of distributed filters are reviewed, the corresponding analysis is systematically addressed, and some interesting results are provided. The inherent purpose of adding consensus terms into the distributed filters is profoundly disclosed. Then, some representative models characterizing various network-induced phenomena are reviewed and their corresponding analytical strategies are exhibited in detail. Furthermore, recent results on distributed filtering with non-Gaussian noises are sorted out in accordance with different network-induced phenomena and system models. Another emphasis is laid on recent developments of distributed filtering with various communication scheduling, which are summarized based on the inherent characteristics of their dynamic behavior associated with mathematical models. Finally, the state-of-the-art of distributed filtering and challenging issues, ranging from scalability, security to applications, are raised to guide possible future research

Isolation and characterization of 13 new microsatellite markers in the triangle mussel (Hyriopsis cumingii)

Microsatellite enriched library of Hyriopsis cumingii was constructed according to the strong affinity between biotin and streptavidin. One hundred clones with foreign inserts were sequenced and 65 clones were screened for usable microsatellites, of which 36 were deemed unique, of sufficient length (more than 8 repeats) and possessed adequate flanking regions for primer designment. Among 36 primer pairs designed, 25 yielded scorable amplification products. Upon testing 30 individuals were sampled using the 25 pair primers from Dongting Lake of Hunan Province, China. Then thirteen polymorphic microsatellite markers were isolated and characterized. These loci exhibited high levels of genetic polymorphism, so the observed number of alleles per locus ranged from 4 to 9. The ranges of observed and expected heterozygosity were 0.2543 to 0.8913 and 0.3629 to 0.8217, respectively, and the average polymorphic information content was 0.5198. Two microsatellite loci were significantly deviated from Hardy-Weinberg equilibrium due to the presence of null alleles, and no linkage disequilibrium found. These microsatellite loci will be useful for assessing the genetic diversity and population structure of H. cumingii

An Improved Stability Criterion of Networked Control Systems

Abstract-The stability criterion of networked control systems with both the network-induced delays and data packet dropouts is investigated. A Lyapunov-Krasovskii functional candidate, which makes use of the information of the lower, upper bounds and the middle point of the time-varying networkinduced delay interval simultaneously, is proposed and a tighter bounding for an integral term of the delay is estimated to drive a less conservative stability condition for networked control systems. No redundant matrix variable is introduced. Finally, two numerical examples are given to show the effectiveness of the proposed stability criterion

SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar

The 4D Millimeter wave (mmWave) radar is a promising technology for vehicle sensing due to its cost-effectiveness and operability in adverse weather conditions. However, the adoption of this technology has been hindered by sparsity and noise issues in radar point cloud data. This paper introduces spatial multi-representation fusion (SMURF), a novel approach to 3D object detection using a single 4D imaging radar. SMURF leverages multiple representations of radar detection points, including pillarization and density features of a multi-dimensional Gaussian mixture distribution through kernel density estimation (KDE). KDE effectively mitigates measurement inaccuracy caused by limited angular resolution and multi-path propagation of radar signals. Additionally, KDE helps alleviate point cloud sparsity by capturing density features. Experimental evaluations on View-of-Delft (VoD) and TJ4DRadSet datasets demonstrate the effectiveness and generalization ability of SMURF, outperforming recently proposed 4D imaging radar-based single-representation models. Moreover, while using 4D imaging radar only, SMURF still achieves comparable performance to the state-of-the-art 4D imaging radar and camera fusion-based method, with an increase of 1.22% in the mean average precision on bird's-eye view of TJ4DRadSet dataset and 1.32% in the 3D mean average precision on the entire annotated area of VoD dataset. Our proposed method demonstrates impressive inference time and addresses the challenges of real-time detection, with the inference time no more than 0.05 seconds for most scans on both datasets. This research highlights the benefits of 4D mmWave radar and is a strong benchmark for subsequent works regarding 3D object detection with 4D imaging radar

LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion

As an emerging technology and a relatively affordable device, the 4D imaging radar has already been confirmed effective in performing 3D object detection in autonomous driving. Nevertheless, the sparsity and noisiness of 4D radar point clouds hinder further performance improvement, and in-depth studies about its fusion with other modalities are lacking. On the other hand, most of the camera-based perception methods transform the extracted image perspective view features into the bird's-eye view geometrically via "depth-based splatting" proposed in Lift-Splat-Shoot (LSS), and some researchers exploit other modals such as LiDARs or ordinary automotive radars for enhancement. Recently, a few works have applied the "sampling" strategy for image view transformation, showing that it outperforms "splatting" even without image depth prediction. However, the potential of "sampling" is not fully unleashed. In this paper, we investigate the "sampling" view transformation strategy on the camera and 4D imaging radar fusion-based 3D object detection. In the proposed model, LXL, predicted image depth distribution maps and radar 3D occupancy grids are utilized to aid image view transformation, called "radar occupancy-assisted depth-based sampling". Experiments on VoD and TJ4DRadSet datasets show that the proposed method outperforms existing 3D object detection methods by a significant margin without bells and whistles. Ablation studies demonstrate that our method performs the best among different enhancement settings

Aqua­{N-[1-(2-oxidophen­yl)ethyl­idene]-l-serinato}copper(II) monohydrate

In the title compound, [Cu(C11H11NO4)(H2O)]·H2O, each CuII ion is four-coordinated by one N and two O atoms from the tridentate Schiff base ligand, and by one O atom from the coordinated water mol­ecule in a distorted square-planar geometry. Inter­molecular O—H⋯O hydrogen bonds link complex mol­ecules and solvent water mol­ecules into flattened columns propagated in [100]