Aiming at the detail rendering in volume data, a new volume illumination model, called Composed Scattering Model (CSM), is presented. In order to enhance different details in volume data, scattering intensity is decomposed into volume scattering intensity and surface scattering intensity with different weight functions. According to the Gauss probability distribution of gray and gradient of data, we propose an accurate method to detect the materials in a voxel, called composed segmentation. In addition, we discuss the principle of constructing these weight functions based on the operators defined in composed segmentation. CSM can generate images containing more details than most popular volume rendering models. This model has been applied to the direct volume rendering of 3D data sets obtained by CT and MRI. The resultant images show not only rich details but also clear boundary surfaces. CSM is demonstrated as an accurate volume rendering model suited for detail enhancement in volume data sets. 相似文献
This paper is concerned with the inversion of confluent Vandermonde matrices. A novel and simple recursive algorithm for inverting confluent Vandermonde matrices is presented. The algorithm is suitable for classroom use in both numerical as well as symbolic computation. Examples are included to illustrate the proposed algorithm. 相似文献
This paper concerns the following problem: given a set of multi-attribute records, a fixed number of buckets and a two-disk system, arrange the records into the buckets and then store the buckets between the disks in such a way that, over all possible orthogonal range queries (ORQs), the disk access concurrency is maximized. We shall adopt the multiple key hashing (MKH) method for arranging records into buckets and use the disk modulo (DM) allocation method for storing buckets onto disks. Since the DM allocation method has been shown to be superior to any other allocation methods for allocating an MKH file onto a two-disk system for answering ORQs, the real issue is knowing how to determine an optimal way for organizing the records into buckets based upon the MKH concept.
A performance formula that can be used to evaluate the average response time, over all possible ORQs, of an MKH file in a two-disk system using the DM allocation method is first presented. Based upon this formula, it is shown that our design problem is related to a notoriously difficult problem, namely the Prime Number Problem. Then a performance lower bound and an efficient algorithm for designing optimal MKH files in certain cases are presented. It is pointed out that in some cases the optimal MKH file for ORQs in a two-disk system using the DM allocation method is identical to the optimal MKH file for ORQs in a single-disk system and the optimal average response time in a two-disk system is slightly greater than one half of that in a single-disk system. 相似文献
As the result of vibration emission in air, a machine sound signal carries important information about the working condition
of machinery. But in practice, the sound signal is typically received with a very low signal-to-noise ratio. To obtain features
of the original sound signal, uncorrelated sound signals must be removed and the wavelet coefficients related to fault condition
must be retrieved. In this paper, the blind source separation technique is used to recover the wavelet coefficients of a monitored
source from complex observed signals. Since in the proposed blind source separation (BSS) algorithms it is generally assumed
that the number of sources is known, the Gerschgorin disk estimator method is introduced to determine the number of sound
sources before applying the BSS method. This method can estimate the number of sound sources under non-Gaussian and non-white
noise conditions. Then, the partial singular value analysis method is used to select these significant observations for BSS
analysis. This method ensures that signals are separated with the smallest distortion. Afterwards, the time-frequency separation
algorithm, converted to a suitable BSS algorithm for the separation of a non-stationary signal, is introduced. The transfer
channel between observations and sources and the wavelet coefficients of the source signals can be blindly identified via
this algorithm. The reconstructed wavelet coefficients can be used for diagnosis. Finally, the separation results obtained
from the observed signals recorded in a semi-anechoic chamber demonstrate the effectiveness of the presented methods . 相似文献
Properly selected transformation methods obtain the most significant characteristics of metal cutting data efficiently and simplify the classification. Wavelet Transformation (WT) and Neural Networks (NN) combination was used to classify the experimental cutting force data of milling operations previously. Preprocessing (PreP) of the approximation coefficients of the WT is proposed just before the classification by using the Adaptive Resonance Theory (ART2) type NNs. Genetic Algorithm (GA) was used to estimate the weights of each coefficient of the PreP. The WT-PreP-NN (ART2) combination worked at lower vigilances by creating only a few meaningful categories without any errors. The WT-NN (ART2) combination could obtain the same error rate only if very high vigilances are used and many categories are allowed. 相似文献
In this paper, genetic algorithm is used to help improve the tolerance of feedforward neural networks against an open fault. The proposed method does not explicitly add any redundancy to the network, nor does it modify the training algorithm. Experiments show that it may profit the fault tolerance as well as the generalisation ability of neural networks.相似文献