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This paper discusses the novel anti-disturbance control algorithm for hypersonic flight vehicle (HFV) models by using neural network (NN) identifier. Different from those existed anti-disturbance results, the unknown exogenous disturbances in HFV models are assumed to be described by the designed NNs with adjustable parameters. Furthermore, the disturbance-observer-based-control (DOBC) algorithm with...
To make full use of the data information and improve the classification performance, a new evidential neural network classifier is proposed and a novel implementation of multiple classifier systems based on the new evidential neural network classifier is presented in this paper. The ambiguous data contained in the training data is considered as a new class — compound class and the training data is...
In this paper, a least squares based on two-step update identification algorithm is established for the Wiener system by introducing a relaxation factor, which controls the relative importance of the two estimation parts. In addition, the convergence performance of the proposed LS-TSU algorithm is then analyzed. It is shown by a numerical example that if the weighting factor is appropriately chosen,...
With the tremendous advances made by Convolutional Neural Networks (ConvNets) on object recognition, we can now easily obtain adequately reliable machine-labeled annotations easily from predictions by off-the-shelf ConvNets. In this work, we present an abstraction memory based framework for few-shot learning, building upon machine-labeled image annotations. Our method takes large-scale machine-annotated...
In this paper, we present a novel and general network structure towards accelerating the inference process of convolutional neural networks, which is more complicated in network structure yet with less inference complexity. The core idea is to equip each original convolutional layer with another low-cost collaborative layer (LCCL), and the element-wise multiplication of the ReLU outputs of these two...
This paper presents a novel large-scale dataset and comprehensive baselines for end-to-end pedestrian detection and person recognition in raw video frames. Our baselines address three issues: the performance of various combinations of detectors and recognizers, mechanisms for pedestrian detection to help improve overall re-identification (re-ID) accuracy and assessing the effectiveness of different...
An improved KNN text classification algorithm based on Simhash has been proposed by introducing Simhash and the average Hamming distance of adjacent texts as a unit, which solves the problems caused by data imbalance and the large computational overhead in the traditional KNN text classification algorithms. Experimental results demonstrate that the proposed algorithm performs a higher precision, a...
Despite the recent success of neural networks in image feature learning, a major problem in the video domain is the lack of sufficient labeled data for learning to model temporal information. In this paper, we propose an unsupervised temporal modeling method that learns from untrimmed videos. The speed of motion varies constantly, e.g., a man may run quickly or slowly. We therefore train a Multirate...
A single frequency erbium-doped fiber laser with an on-chip high-Q silicon nitride (Si3N4) microring cavity is demonstrated. The laser linear cavity is composed of a microring with a Q of up to 2.5×105 and a free spectral range (FSR) of 2 nm, a 12 cm erbium-doped fiber and a fiber Bragg grating (FBG). The linewidth of 8 kHz is achieved.
Simulation of a permanent magnet synchronous motor (PMSM) servo system which was based on active disturbance rejection controller (ADRC) was presented in this paper. A new Monte-Carlo method for parameter tuning was invented, which was based on different parameter values and their corresponding dynamic performance. What's more, according to the simulation results of the servo system, the ADRC controller...
This paper is aimed to study the fluctuation of the instantaneous availability (IA) for the two-unit series repairable system. The system is based on the renewal model with two states (up and down) under exponential distribution. By Laplace transformation, the analytic solution can be worked out. According to the fluctuation theories, the fluctuation of IA is analysed. Some figures are provided to...
Edge detection is one of the most important tasks in image processing and pattern recognition. Edge detector with multiple color channels can provide more edge information. However, the uncertainty occurring with the edge detection in each single channel and the discordance existing in the fusion of multiple channels edge detectors make the detection difficult. In this paper, we propose a new edge...
Support vector machine (SVM) is a popular machine learning method and has been widely applied in many real-world applications. Since SVM is sensitive to noises, fuzzy SVM (FSVM) has been proposed to relieve the over-fitting problem caused by noises through assigning a fuzzy membership to each sample. Then, different samples make different contributions to the learning of classification hyperplane...
A multi-source image registration algorithm based on combined line and point features is proposed for images containing typical line objects. Firstly, the image control line features are extracted for coarse registration by the use of visual saliency and Line Segment Detection (LSD). Visual saliency represents human visual characteristics. LSD has attributes including rotation invariance, illumination...
Dempster-Shafer evidence theory (DST) is a theoretical framework for uncertainty modeling and reasoning. The determination of basic belief assignment (BBA) is crucial in DST, however, there is no general theoretical method for BBA determination. In this paper, a method of generating BBA using fuzzy numbers is proposed. First, the training data are modeled as fuzzy numbers. Then, the dissimilarities...
Dempster-Shafer theory (DST) is an important theory for information fusion. However, in DST how to determinate the basic belief assignment (BBA) is still an open issue. The interval number based BBA determination method is simple and effective, where the features of different classes' samples are modeled using the interval numbers, i.e., an interval number model is constructed for each focal element...
Cascading failure are common in the large scale circuit system. We apply a cascading failure model to a circuit system, which is based on the flow redistribution. The vulnerability and robustness of a circuit system is studied by using the model under two initial failures: the random failure and the max-load failure. The results show that a single-point failure can influence the system performance,...
Researchers have done extensive work on establishing an accurate user profile, which has been verified an effective way to implement the user marketing accurately and effectively. In this paper, we will present a feature extraction method based on the fusion of Word2Vec and TF-IDF, and try to establish a user profile. The vector space model (VSM) contains the word vector calculated by Word2Vec, and...
Public cultural sharing service plays an important role in the public cultural platform. The recommender systems can bring users useful cultural resources and information. For safety and security reasons of the cultural resources, the external applications are not allowed to directly access the original resource data stored in the cultural databases by sending recommendation requests. The cultural...
In this letter, low-voltage unipolar inverter based on solid-state silica electric-double-layer (EDL) top-gate thin-film transistors was fabricated. A silicon oxide film deposited by the plasma-enhanced chemical vapor deposition method at room temperature was used as inorganic electrolyte insulator. Due to the formation of the EDL, the inverter can work at low voltages that are less than 1 V. The...
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