Different from previous studies on memristive chaotic oscillators which tended to adopt common mathematical models but lacked practical consideration, in this paper, a novel memristive chaotic oscillator based on a mo...
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Different from previous studies on memristive chaotic oscillators which tended to adopt common mathematical models but lacked practical consideration, in this paper, a novel memristive chaotic oscillator based on a modified voltage-controlled HP memristor model was proposed for the first time. By replacing Chua's diode with this model in a canonical Chua's circuit, we derived an oscillator characterized by rich dynamics such as special-shaped attractors, a wide range of chaos and insensitivity to the initial value of the memristor. These features were systematically investigated in terms of bifurcation diagrams, Poincaré map, time series, Lyapunov exponents, etc.
For speech emotion recognition, emotional feature set with high dimension may produce redundant features and influence the recognition accuracy. To solve this problem and obtain the optimal emotional feature subset of...
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For speech emotion recognition, emotional feature set with high dimension may produce redundant features and influence the recognition accuracy. To solve this problem and obtain the optimal emotional feature subset of speech, a feature dimension reduction based on linear discriminant analysis is proposed. According to the confusion degree between different basic emotions, an emotion recognition method based on support vector machine decision tree is proposed. Experiment on speaker-dependent speech emotion recognition using Chinese speech database from institute of automation of Chinese academy of sciences is performed and a speech emotion recognition system is presented, where standard feature sets of the INTER-SPEECH and classic classifiers are used in comparative experiments respectively. Experimental results show that the proposal achieves 84.39% recognition accuracy on average. By proposal, it would be fast and efficient to discriminate emotional states of diverse speakers from speech, and it would make it possible to realize the interaction between speaker and computer/robot in the future.
During the drilling process, accurate prediction of drilling efficiency and safety plays a key role in timely adjustment of drilling process state. In general, surface parameters rate of penetration(ROP) and mud pit v...
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During the drilling process, accurate prediction of drilling efficiency and safety plays a key role in timely adjustment of drilling process state. In general, surface parameters rate of penetration(ROP) and mud pit volume(MPV) are often used as important parameters to judge drilling safety and efficiency due to the bad bottom hole environment and unreliable detection devices. However, most drilling systems are underground, the structure is complex and exists many disturbances, so the state of drilling process is difficult to accurately predict. In this paper, an online support vector regression(OSVR) model is proposed to predict the ROP and MPV. First, the parameters of the model are determined by simple drilling process analysis. Then, the fast fourier transform filtering method is used to filter the high frequency disturbances of the data. Finally, the prediction model is established by support vector regression(SVR) method and the model is continuously updated by the model update method. The simulation results of industrial data show that the proposed model has a good prediction effect.
To identify some special formation lithology with imbalanced logging data, a framework of Multi-layer lithology identification method is proposed. In this framewoke, some special lithology is divided into one class in...
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To identify some special formation lithology with imbalanced logging data, a framework of Multi-layer lithology identification method is proposed. In this framewoke, some special lithology is divided into one class in the first layer, and each lithology is separated in the second layer. A novel algorithm of AdaCost2-support vector machine (AdaC2-SVM) is put forward using logging data of actual well located in Karamay for training, and the support vector machine-recursive feature elimination (SVM-RFE) is adopted to select attribute, and logging data from another well nearby is used for testing. Experiment result shows the G-mean and accuracy of our method is up to 95.3% and 94.4%, which has better performance than random forest(RF) algorithm, particle swarm optimization-support vector machine (PSO-SVM) algorithm and improved PSO-SVM(IPSO-SVM) algorithm. In the future, the proposed method have a good prospect and give a valuable result for geology research.
Aiming at the detection of moving objects in video series, a moving object detection algorithm based on background difference method and inter-frame difference method is proposed. A new background update method is pro...
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Aiming at the detection of moving objects in video series, a moving object detection algorithm based on background difference method and inter-frame difference method is proposed. A new background update method is proposed to update the unchanged background area into the background frame. Experiments show that this method overcomes the problems of false detection and empty in the previous detection algorithms. The method can meet the need of real-time detection and tracking of moving targets with the advantages of high accuracy and fast calculation speed.
A demand analysis method based on TAKAGI-SUGENO (T-S) fuzzy model for drinking service is proposed to provide corresponding services according to users' emotions and intentions in human-robot interaction, in which...
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A demand analysis method based on TAKAGI-SUGENO (T-S) fuzzy model for drinking service is proposed to provide corresponding services according to users' emotions and intentions in human-robot interaction, in which T-S fuzzy model is used to establish the relationship among human intention and human demands. First, the transformation of input and output is discussed. Secondly, fuzzy rules are formulated, and then fuzzy inference is applied to get user's demand corresponding to emotion and intention. The proposal considers peoples fuzziness in inferring humans intention, which could help the robots to provide satisfied drinking service to users. To validate the proposal, drinking service experiments are performed in a laboratory scenario using a humans-robots interaction system, from which the experimental results demonstrate the feasibility of the proposal.
As slide steering technology has lower maintenance costs, it is widely used in geological drilling industry. In order to adjust the hole trajectory, this technology changes the drilling direction by controlling tool f...
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As slide steering technology has lower maintenance costs, it is widely used in geological drilling industry. In order to adjust the hole trajectory, this technology changes the drilling direction by controlling tool face angle of downhole power drill tool. However, due to the existence of the untwist angle, it is difficult to precisely control the angle, which will directly affect the quality of hole trajectory. So untwist angle prediction is the prerequisite of hole trajectory control. This paper introduces a common method for calculating untwist angle for generating the training set. And then factors that influence untwist angle will be analyzed. Meanwhile, based on the analysis and calculation results, support vector regression is introduced in the prediction algorithm to provide a new way for untwist angle prediction.
In order to avoid the linear inversion method falling into local minima and slow convergence speed of the global optimization inversion method, the article proposed the simplex-simulated annealing algorithm for transi...
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In order to avoid the linear inversion method falling into local minima and slow convergence speed of the global optimization inversion method, the article proposed the simplex-simulated annealing algorithm for transient electromagnetic inversion research which combines advantages of the simplex method and the simulated annealing algorithm. The simplex method is used to obtain local minimum value which is relatively close to the actual value, then the simulated annealing algorithm is used to obtain the global optimal solution which can better reflect structural characteristics of the real stratigraphic model. Through the comparison of the noise inversion results and noise free inversion results about K-type, H-type, KH-type and HKH-type stratigraphic models, it can be proved that the simplex-simulated annealing algorithm can suppress some noise. The comparison of the simulated annealing method and the simplex-simulated annealing algorithm shows that the simplex-simulated annealing algorithm has the characteristics of global searching ability and fast convergence speed.
Maximum power point tracking controller is essential to obtain the maximum power from a solar array in the photovoltaic systems as the PV power module varies with the temperature and solar irradiation. In the DC/DC ci...
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Maximum power point tracking controller is essential to obtain the maximum power from a solar array in the photovoltaic systems as the PV power module varies with the temperature and solar irradiation. In the DC/DC circuit, the maximum power point tracking algorithm based on parabolic approximation method is used. On the basis of analyzing the principle of various tracking methods, the key technology of parabola approximation can be found to find the exact maximum power point.
With the application of magnetic thin films becoming more and more widespread, people pay more and more attention to the performance characterization. In order to obtain a magnetic film with a specific performance, it...
With the application of magnetic thin films becoming more and more widespread, people pay more and more attention to the performance characterization. In order to obtain a magnetic film with a specific performance, it is very important to judge the quality of the magnetic film and measure the magnetic properties of the film. However, with the increase of the film preparation process, the thickness of the prepared film is getting thinner and the magnetic moment signal contained therein is also decreased. This brings a certain degree of difficulty to the traditional measurement methods. For example, the VSM system that obtains the hysteresis loop by measuring the magnetic moment signal has become somewhat inadequate for the measurement of ultra-thin films. In order to solve this issue, a new method based on anomalous Hall effect is introduced in this paper. The test system of this system adopts the four-probe measuring method, a constant current is applied across the surface of the film sample, and the abnormal Hall voltage is measured at the other two ends. The R-H curve of the sample can be obtained through calculation. As compared to VSM measurement, this method is simpler and stable, more accurate, which can greatly reduce the anomalous Hall-effect device R-H characteristic measurement cost.
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