A new method of management and scheduling is pointed out to solve a key problem what is management and scheduling of event in general training systems. Firstly, every event is classified depended on the kinds of feder...
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ISBN:
(纸本)9781604239232
A new method of management and scheduling is pointed out to solve a key problem what is management and scheduling of event in general training systems. Firstly, every event is classified depended on the kinds of federates and indicated the trigger-relation. Secondly, a XML-based training scenario through the combination of the workflow and conceptions in HLA is compiled. an event engine is designed on the basis of the training scenario, being responsible for the scheduling of events which are in and between federates. A practical example of a training system for crisis management was presented to introduce the particular process of the design and implement.
This paper proposes a new image denoising method which exploits spatial correlation among image wavelet coefficients and classification *** extending the neighbouring threshold of wavelet coefficients for 1D signal to...
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This paper proposes a new image denoising method which exploits spatial correlation among image wavelet coefficients and classification *** extending the neighbouring threshold of wavelet coefficients for 1D signal to 2D image case,each coefficient in a subband is classified as "large" or "small" category,according to its corresponding neighbouring *** strategies are implemented to the classified *** results show that although very simple,the performance of the proposed method can be competitive to the two excellent state of the art denoising algorithms with spatial adaptivity.
This paper presents a super performance bandgap voltage reference for DC-DC converter with adjustable output. It generates a wide range of voltage reference ranging from sub-1 V to 1.2217 V and has a low temperature c...
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This paper presents a super performance bandgap voltage reference for DC-DC converter with adjustable output. It generates a wide range of voltage reference ranging from sub-1 V to 1.2217 V and has a low temperature coefficient of 2.3 × 10-5/K over the temperature variation using the current feedback and resistive subdivision. In addition, the power supply rejection ration of the proposed bandgap voltage reference is 78 dB. When supply voltage varies from 2.5 V to 6 V, output VREF is 1.221685 ± 0.055 mV.
The purpose of this paper is to study spatiotemporal patterns of neuronal activity in emotional processing by analysis of ERP data. 108 pictures (categorized as positive, negative and neutral) were presented to 24 hea...
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ISBN:
(纸本)0819461865
The purpose of this paper is to study spatiotemporal patterns of neuronal activity in emotional processing by analysis of ERP data. 108 pictures (categorized as positive, negative and neutral) were presented to 24 healthy, right-handed subjects while 128-channel EEG data were recorded. An analysis of two steps was applied to the ERP data. First, principal component analysis was performed to obtain significant ERP components. Then LORETA was applied to each component to localize their brain sources. The first six principal components were extracted, each of which showed different spatiotemporal patterns of neuronal activity. The results agree with other emotional study by fMRI or PET. The combination of PCA and LORETA can be used to analyze spatiotemporal patterns of ERP data in emotional processing.
This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the...
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This paper describes the scale invariant feature transform (SIFT) method for rapid preregistration of medical image. This technique originates from Lowe's method wherein preregistration is achieved by matching the corresponding keypoints between two images. The computational complexity has been reduced when we applied SIFT preregistration method before refined registration due to its O(n) exponential calculations. The features of SIFT are highly distinctive and invariant to image scaling and rotation, and partially invariant to change in illumination and contrast, it is robust and repeatable for cursorily matching two images. We also altered the descriptor so our method can deal with multimodality preregistration
Mutual information (MI) is an effective criterion for multi-modal image registration. However the traditional MI function only includes intensity information of images and lacks sufficient spatial information to accur...
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Mutual information (MI) is an effective criterion for multi-modal image registration. However the traditional MI function only includes intensity information of images and lacks sufficient spatial information to accurately measure the degree of alignment of two images, and besides, it is apt to be influenced by intensity interpolation, therefore presents many local maxima which frequently lead to misregistration. Our paper proposes a criterion of adaptive combination of intensity and gradient field mutual information (ACMI). Unlike the intensity MI computed from two original images, the gradient field MI of two images is calculated from their gradient code maps (GCM) constructed by coding the gradient field information of corresponding original image. Because of their complementary properties, these two MI functions are combined to form ACMI by a nonlinear weight function which can be adaptively regulated according to their performances and make the better dominant in the combination. Experimental results demonstrate that the ACMI outperforms the traditional MI and furthermore the former is much less sensitive than the latter to the reduction of resolution or overlapped region of images
Multisensor information plays an important pole in the target recognition and other application fields. Fusion performance is tightly depended on the fusion level selectes and the approach used. Feature level fusion i...
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Multisensor information plays an important pole in the target recognition and other application fields. Fusion performance is tightly depended on the fusion level selectes and the approach used. Feature level fusion is a potential and difficult fusion level. Bayesian fusion method is an important theory in feature level. A new method is presented to fuse infrared images and recognize object in the paper. Firstly,Bayesian principles, fusion mode and recognition decision function are described. Then, aiming at the features of mid-wave infrared image and long-wave infrared image, we use Bayesian probability to fuse them. Last, recognize target and background obtained with training and test pattern vectors. The experiment results show stability and feasibility of the fusion recognition using Bayesian decision theory in infrared image.
According to the features of mid-wave and long-wave infrared images,they are decomposed into morphology pyramid respectively based on the new multiscale mathematical morphology filters proposed in the *** features suc...
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According to the features of mid-wave and long-wave infrared images,they are decomposed into morphology pyramid respectively based on the new multiscale mathematical morphology filters proposed in the *** features such as local maximum gray level and average gradient strength of every image are extracted at each level of morphology *** dualband infrared images based on fusion rule put forward in the paper,and then reconstruct original image and detect target using contrast threshold *** experiment results show that dualband infrared images target detection algorithm based on multiscale morphology algorithm is better than use mid-wave or long-wave infrared images detect targets alone.
A DSP/FPGA-based parallel architecture oriented to real-time imageprocessing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnec...
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A DSP/FPGA-based parallel architecture oriented to real-time imageprocessing applications is presented. The architecture is structured with high performance DSPs interconnected by FPGA. Within FPGA a FIFO interconnection network and the specific data communication protocol are implemented, which interconnect 3 DSPs (TMS320C6414) effectively. The measured performances in the prototype with the proposed parallel architecture, including inter-DSP data communication performance and system computing capacity, show high data transfer bandwidth (up to 400 Mbytes/s) with low latency as well as high imageprocessing performance, which achieve a good balance for parallel imageprocessing
This paper proposes a new image denoising method which exploits spatial correlation among image wavelet coefficients and classification technique. By extending the neighbouring threshold of wavelet coefficients for 1D...
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This paper proposes a new image denoising method which exploits spatial correlation among image wavelet coefficients and classification technique. By extending the neighbouring threshold of wavelet coefficients for 1D signal to 2D image case, each coefficient in a subband is classified as "large" or "small" category, according to its corresponding neighbouring threshold. Different strategies are implemented to the classified coefficients. Simulation results show that although very simple, the performance of the proposed method can be competitive to the two excellent state of the art denoising algorithms with spatial adaptivity
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