Papers by Author: Hong Wang

Abstract: This paper introduces an effective face detection method based on log-Gabor filters. First, Information contained in the log-Gabor transformations is analyzed. Next, 5-scale and 8-orientation log-Gabor filters are constructed to extract feature vectors. Then, a three-layer feedforward network is created for feature classification. After training the network, we test 80 samples. From the experimental result, log-Gabor filters based method has comparable detection performance with Gabor filters based method. Therefore, log-Gabor filters can encode the images more efficiently.

Abstract: In this paper, based on the output feedback decoupling, curve fitting and spline interpolation method, a mathematical model is presented for nonlinear dynamical system wherein only system inputs and outputs are known.

Abstract: A kind of stimulation device aiming at alleviating brain fag was designed. Meanwhile, the specific stereo signal which is expected to induce alpha-wave of human brain was programmed and encoded into audio files. To evaluating the effectiveness of this system, a comparison test was conducted. Volunteers are divided into control group and experimental group. Via power spectral analyzing, we can find the difference of EEG signals between control group and experimental group in alpha band (8~13Hz). It can be noted that the intensity of alpha-wave and beta-wave of experimental group is larger than that of control group obviously.

Abstract: The cerebral blood flow velocity (CBFV) of middle cerebral artery (MCA) was detected during the fatigue driving using Transcranial Doppler. The CBFV was also analyzed after the fatigue driving by different means of relaxation to alleviate brain fatigue. The results show that the CBFV in MCA is reduced by driving fatigue.

Abstract: Volume rendering can be used to exhibit the shape and volumetric properties of 3-D objects. However, it requires a considerable amount of time to process the large volume of data. In this article we present a speed-up method by pre-computing some data of the shading model. We index voxel surface normal by and in spherical coordinate system. Each voxel surface normal is pre-computed and stored in array of values [ ]. Some values of the shading model related to voxel surface normal and light vector are also stored. Each rendering we only need updating these values for shading calculation. We found that our speed-up method can reduce about one fourth of computing time but need less additional memory to store surface normal using this spherical index method.

Abstract: It introduces a design of the control system for rehabilitation horse based on MCU STC89C52. The system’s control core is an 8-bit MCU STC89C52. First, the user input commands through the keyboard, then send commands to the DA conversion chip PCF8591 which can achieve the digital signal to analog signal output after dealing with MCU. Finally, PCF8591 send analog signal to the speed controller of DC motor in order to control the DC motor’s speed. Meanwhile, it builds a human-machine interface (HMI) to display the real-time speed of the horse through LCD.

Abstract: The traditional PID control in nonlinear system such as high-speed wind tunnel has limitations, and the range of using is limited. The BP neural network has been widely applied to the optimization of the PID controller parameter adjustment. The PID neural network control system is introduced in the conventional PID control, which has advantages such as simple structure, physical meaning clear parameters, but also has a neural network of parallel structure and the function of learning and memory and nonlinear mapping capability. The controller uses BP (error back propagation) algorithm to correct connection weights, through on-line training and learning and make objective function to achieve optimal value. This improvement scheme can not only improve algorithm in the training process, and the convergence speed in the wind tunnel, the control valve control system response speed, high precision, meet the steady-state real-time control requirements.

Abstract: Ocular artifacts are the most important form of interferences in EEG signals. Before analyzed, EEG signals should be pretreated by removal of ocular artifacts. CICA is an excellent approach to separate the desired source signals. But, the choice of reference signals is crucial. In this paper, we adopted CICA to separate ocular artifact from EEG, using a different method from Lu to build the reference signals, which can avoid the subjectivity during the operation. It was proved to be effective.

Abstract: It was much more complex and difficult for off-line signature identification attributable to the limitation of available information. To solve the problem, a signature identification method based on strength and strokes direction was proposed. The signature image acquired was gray-scaled and filtered at the stage of preprocess; then the image was two-valued with different threshold based on strength feature, the regions which grayscale was less than threshold were retained; the strokes which possess distinctive directional feature were extracted by using mathematical morphology and combining different scales/directions structure element based on strokes direction feature; at last judgement was maked for sample in accordance with corresponding feature. Experimental results showed the proposed method can enhance accurate rate effectively, improve real-time performance, which was a try beneficial to apply new methods for off-line signature identification.