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The experimental results show that the quantization errors of different wavelet bases are usually different and the wavelet base of the minimum quantization error in space and frequency domain is 5/3 wavelet after exchanging the decomposition and reconstruction filters.

实验结果表明不同小波基的量化误差通常是不同的,具有最小空、频域量化误差的小波基是交换分解和重构滤波器后的5/3小波。

A piece of quartic spline curve was constructed and the same analysis was applied to it as well for comparison.

给出一个拐角重构实例,插补构建的曲线,并分别分析了插补输出的速度、加速度及加加速度。

In this paper, a simple interpolation method using quartic polynomials to fill in the missing projections is presented. The clipping on the pixel values of the reconstructed image is also proposed.

为了消除这种金属伪影,提出了一种用四次多项式来对缺失的投影值进行插值,并对重构的图象进行值裁剪的方法。

Firstly, image is decomposed into two serials, which are predicted and updated by two-order Neville filter on rectangle and quincunx grid by turns.

首先将图像分解为两个序列,用2阶Neville滤波器构造预测和更新算子,对两个序列以矩形栅格和梅花形栅格的格式进行交替预测和更新;再以各个波段的方差作为融合的特征,进行特征级第二代小波加权融合,最后对图像进行第二代小波重构

A novel multisensor images fusion algorithm is presented based on lifting quincunx wavelt. First, the lifting quincunx wavelet transform is used to perform a multiscale decomposition of each image. Then, the wavelet coefficients of fused image are constructed using multiple operators according to different fusion rules. Finally, the reconstructed image is obtained through the inverse transform.

提出了一种基於提升方案的五株形小波的多传感器图像融合方法,即在提升五株形小波多尺度分解的基础上,对每一幅图像进行多尺度分解,按照不同的融合规则和融合运算子去构造融合图像对应的各小波系数,再通过逆变换重构融合后的图像。

The results indicate that the reconstructed quintic spline curve can ensure the cutter transit well for corner contour, and that the cutting performance is superior to that of the quadratic one.

同时也重构了一条四次样条曲线与五次样条曲线作对比分析,结果表明,五次曲线能使裁刀获得良好的且较四次曲线优越的轮廓拐角加工性能。

Keywords leather cutting;corner reconstruction;quintic spline curve;motion stability

皮革裁剪;拐角重构;五次样条曲线;运动平稳性

A hybrid model of short-term load forecasting based on chaotic theory, correlation and neural networks is presented in this paper. Firstly, reconstruct attractors in phase spaces using chaotic theory, Secondly fit the attractor's evolvement using BP neural networks, because selecting neural network's input training data using Euclid distance and correlation, improve neural network's associative memory and ratiocinative ability, can better fit the attractor's evolvement.

提出一种将混沌理论、关联度和神经网络相结合的短期负荷预测模型,首先利用混沌理论重构负荷时间序列的相空间吸引子,然后用BP 神经网络来拟合空间吸引子的演化,由于使用空间欧氏距离和关联度联合来选取神经网络的训练样本,这样就提高了神经网络对负荷序列混沌特性的联想和泛化推理能力,能够更好的拟合吸引子的演化。

Firstly, reconstruct attractors in phase spaces using chaotic theory,Secondly fit the attractor s evolvement using BP neural networks, because selecting neural network s input training data using Euclid distance and correlation, improve neural network s associative memory and ratiocinative ability, can better fit the attractor s evolvement.

提出一种将混沌理论、关联度和神经网络相结合的短期负荷预测模型,首先利用混沌理论重构负荷时间序列的相空间吸引子,然后用BP神经网络来拟合空间吸引子的演化,由于使用空间欧氏距离和关联度联合来选取神经网络的训练样本,这样就提高了神经网络对负荷序列混沌特性的联想和泛化推理能力,能够更好的拟合吸引子的演化。

The fundamental reactive current component is evaluated by the reconstruction of the phase difference between the fundamental component and the power source voltage.

通过重构基波分量与电源电压之间的相位差,求得了信号中的基波无功电流分量。

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