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Currently the UAV photographic data is unstable, turbulent and inaccurate, and these flaws make image stitching difficult. This paper proposed an innovative fast method based on global subdivision GeoSOT grid frame. And this method can apply to the high-speed image stitching of a certain area at different times on the UAV. The experiment result shows the advantages of the new method over the traditional...
Accent is a critical important component of spoken communication, which plays a very important role in spoken communication. In this paper, we conduct accent by using RASTA - PLP algorithm to extract short-time spectrum features of each speech segment based on sub-segment splicing information. We build short-time spectrum feature sets based on RASTA - PLP algorithm. And we choose NaiveBayes classifier...
In order to achieve online monitoring the downhole information related to ESP working state, an ESP downhole parameters monitoring system based on current loop data transmission method was developed. Compared with other methods, the current loop data transmission method is relatively insensitive to interference in harsh environment. By means of ESP motor's winding and symmetrical reactance located...
Enormous amount of unstructured electronic health record are invaluable for the medical research in finding the relationship between the patient's disease and the final diagnosis. How to use computer automatically dig up these information has long been a hot spot. To get the relationship between the clinical outcomes and free text writing by nurse, we developed an automatic categorization system process...
Question classification is an important part of Chinese question answering system, and the result of question classification directly affects the quality of question answering. This paper presents a new method on feature extraction for question classification. HowNet and dependency parsing are used in this new method. The classification experimental results using SVM classifier have shown that the...
The discrimination and supervision of insider trading and market manipulation is very hard because of the cover-up used and the large trading data. So this paper firstly analyses the impact of insider trading and market manipulation on the security market. Based on it, we set up the discrimination model with probabilistic neural network, and use it to discriminate the insider trading and market manipulation...
In stamping process, springback is always determined by process parameters, such as blank-holder force, mould parameters, material parameters, and so on. Prediction of springback and parameters is a multi-objective optimization problem. Firstly, based on the same quantity of orthogonal experimental samples, prediction accuracy and efficiency of back propagation neural network (BPNN) prediction model...
In the deep-drawing process of sheet metal, accuracy, consistency and formability of products always determined by the variable blank holder force (VBHF). So, the accuracy of predicted reference input VBHF curves, the response performance of hydraulic actuators, and the tracing performance of machine controller are key technologies which determine the control performance of VBHF. Firstly, outline...
In this paper we firstly introduce the basic principle of FFT and analysis practical engineering requirement of electrical network monitoring. Secondly, we build hardware platform based on TMS320F2812 DSP and C28x FFT transform library provided by TI, accomplish the method of floating-point operations on fixed-point DSP, and convert time-domain signals into frequency-domain signal by FFT. Then electrical...
Passenger traffic forecast is significant for the study of the change of passenger transport capacity. Forecasting passenger traffic scientifically is very important for decision-making of transportation development strategies. This paper analyzes the factors of passenger traffic, and describes the principle of the grey-Markov chain. Then we divide these factors into two categories: supply factors...
Based on radial basis function (RBF) kernel, a new self-adaptive method to optimize the least squares support vector machines (LS-SVM) parameters, the width of kernel parameter sigma and the LS-SVM regularization parameter gamma are proposed. Detailed methodology steps of this algorithm method are presented. Compared with back propagation neural networks (BPNN), various simulation experiments for...
A fault diagnosis method for analog circuits based on Support Vector Machine (SVM) and AdaBoost algorithm is developed in this paper. Firstly, output voltage signals from the test nodes are obtained from analog circuits test points and the fault feature vectors are extracted from Haar wavelet packet transform coefficients. Then, after training the AdaBoost SVM by faulty feature vectors, the SVM ensemble...
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