Automatic modulation classification (AMC) plays a key role in non-cooperative communication systems. Feature-based (FB) methods have been widely studied particular. Most existing FB are deployed at fixed SNR level, and the pre-trained classifiers may no longer be effective when level changes. The also need to re-trained suitable for varying channel environment. To address these problems, robust AMC method under noise conditions is proposed this paper. attempts select noise-insensitive...

With the continuous development of artificial intelligence, embedding object detection algorithms into autonomous underwater detectors for marine garbage cleanup has become an emerging application area. Considering complexity environment and low resolution images taken by detectors, this paper proposes improved algorithm based on Mask R-CNN, with aim achieving high accuracy instance segmentation. First, idea dilated convolution is introduced in Feature Pyramid Network to enhance feature...

We present a nonparametric statistical framework for the quantification, analysis, and propagation of data uncertainty in direct volume rendering (DVR). The state-of-the-art DVR allows preserving transfer function (TF) ground truth when visualizing uncertain data; however, existing is restricted to parametric models uncertainty. In this paper, we address limitations by extending distributions. exploit quantile interpolation technique derive probability distributions representing viewing-ray...

Transfer function (TF) design is a central topic in direct volume rendering. The TF fundamentally translates data values into optical properties to reveal relevant features present the volumetric data. We propose semi-automatic scheme which consists of two steps: First, we clustering process within 1D/2D domain based on proximities respective spatial domain. presented approach provides an interactive tool that aids users exploring clusters and identifying interest (FOI). Second, our method...

Numerical Weather Prediction (NWP) ensembles are commonly used to assess the uncertainty and confidence in weather forecasts. Spaghetti plots conventional tools for meteorologists directly examine exhibited by ensembles, where they simultaneously visualize isocontours of all ensemble members. To avoid visual clutter practical usages, one needs select a small number informative isovalues analysis. Moreover, due complex topology variation isocontours, it is often challenging task interpret...

In order to perform competitive privacy-guaranteed object detection, we propose an end-to-end model called Privacy-preserving Deep Transformation Self-attention (PPDTSA). This ensures the privacy of inference results. It has a low-complexity hierarchical structure with relatively small number hyper-parameters. Consistency prediction is achieved through encoding and decoding blocks self-attention mechanism which enables points interest be located. Focus loss estimated based on...

Orthogonal frequency division multiple access (OFDMA), which is widely used in the wireless sensor networks, allows different users to obtain subcarriers according their subchannel gains. Therefore, how assign and power achieve a high system sum rate an important research area OFDMA systems. In this paper, focus of study on adaptive (RA) based resource allocation with proportional fairness constraints. Since NP-hard non-convex optimization problem, new efficient algorithm ACO-SPA proposed,...

Multi-scale approach representing image objects at various levels-of-details has been applied to computer vision tasks. Existing classification approaches place more emphasis on multi-scale convolution kernels, and overlook feature maps. As such, some shallower information of the network will not be fully utilized. In this paper, we propose Multi-Scale Residual (MSR) module that integrates maps underlying last layer Convolutional Neural Network. Our proposed method significantly enhances...

In this paper, a new kind of porous metal fiber sintered sheet (PMFSS) with high porosity was fabricated cutting stainless steel fiber.And heat transfer experiments were conducted to investigate the effect and flow rate on properties PMFSS.Metal fibers formed three-dimensional reticulated structure numerous connected micro pore structures in PMFSS during sintering process Test results showed that coefficient increases increasing 80% sample shows best performance.And pressure drop decreasing...

In this paper, a kernelized version of nonparametric discriminant analysis is proposed that we name KNDA. The main idea to first map the original data into another high dimensional space, and then perform in space. Nonparametric can relax Gaussian assumption required for classical linear analysis, Kernel trick further improve separation ability. A group tests on several UCI standard benchmarks have been carried out prove our method very promising.

In this paper, we propose a novel 3D head model retrieval approach in which the queries are 2D face views instead of less readily available models. The basic idea is to characterize corresponding relations between view feature and based on machine learning approach. Thus subsequent matching can be carried out space. As an effective solution regression problems, relevance vector used paper establish association features. Experimental results show that our proposed query method comparable with...

Abstract The ideal linear elastic, small hysteresis phenomenon makes the quartz resonator uniquely useful for Quartz Crystal Microbalances (QCM). Enhanced high‐precision integrated crystal resonators were designed based on common‐mode rejection principle. internal stress of force was analyzed multielectrode design, and point which located electrode (diameter is 1 mm) distributed circle from 4 mm to center plate, orientation angle φ=60°. 15 group difference frequency signals first done...

In this paper, a novel 3D head model retrieval framework is proposed. First, kernel PCA adopted both to reduce the data dimension and extract features for characterization. Second, based on derived features, hierarchical indexing structure database constructed using self organizing map (HSOM). Third, an efficient search approach presented established that requires only feature matching between query small number of SOM nodes. The main advantages our include high precision due discrimination...

Environmental protection is still a key issue that cannot be ignored at this stage of social development. With the development artificial intelligence, various technologies increasingly tend to widely used in field environmental protection, such as searching wilderness through an unmanned aerial vehicle (UAV) and cleaning garbage by robots. Traditional object detection algorithms for scenario suffer from low accuracy high computational cost. Therefore, paper proposes algorithm applied...

Space formation aircraft communication system needs to meet strong anti-interference ability, low power consumption and high transmission rate performance. Ultra-wideband (UWB) has data transfer rate, device complexity, interference resistance confidentiality. Therefore, UWB technology is used in space system, which direct sequence ultra-wideband (DS-UWB) system. This paper, we put forward a multi-user detection (MUD) algorithm based on Gaussian Mixture Model (GMM) DS-UWB its...

Ultrawide bandwidth (UWB) positioning technique is one of the most important alternatives for and navigation when prevailing global satellite systems (GNSS) are not reliable. We looked into troublesome dense multipath problems multiuser interference (MUI) in indoor environment. This paper describes a novel ranging scheme using waveform division multiple access UWB (WDMA-UWB) joint TOA estimation. The estimation combines coherent detection entropy-based orthogonal pulses WDMA-UWB can provide...

In this paper, an Radial Basis Function (RBF) network based Ultra-Wide Band modulation scheme recognition algorithm is proposed. the UWB receiver, statistical characterization parameters of signal after A/D converter are extracted as input neuron layer. Experiments show that RBF can achieve good performance. The probability correct with proper parameter spread higher than 95% at 10dB SNR condition. Compared traditional pattern and statistics judgment algorithms, recognizer classify...

With the general availability of 3D digitizers and scanners, graphical models have been used widely in a variety applications. This has led to development search engines for models. Especially, head model classification retrieval received more attention view their many potential applications criminal identifications, computer animation, movie industry medical industry. paper addresses problem using 2D subspace analysis methods such as principal component (2D PCA[3]) fisher discriminant...

In this paper, we introduce a new approach for the classification of point-based 3D computer graphics models. We propose representation point cloud models based on set principal projection axes. The is then projected to each these axes, and suitable summary statistics along axis calculated. complete adopted as feature set. Based representation, need search optimal axes which can best distinguish different classes in database. general, optimization problem difficult due size space. As result,...