在高光谱图像(HSI)恢复中,如何在模型中有效嵌入先验信息和正确建模噪声一直是研究的两个重点。边信息作为一种基于域的先验知识已经在许多方向取得了成功,然而在高光谱去噪领域仍未受到关注。为了将这种领域知识与高光谱恢复模型自然耦...在高光谱图像(HSI)恢复中,如何在模型中有效嵌入先验信息和正确建模噪声一直是研究的两个重点。边信息作为一种基于域的先验知识已经在许多方向取得了成功,然而在高光谱去噪领域仍未受到关注。为了将这种领域知识与高光谱恢复模型自然耦合,提出的方法采用双线性映射的方式将边信息链接到表示观测数据潜在低秩结构的底层矩阵,并使用E-3DTV(enhanced 3-D total variation)正则编码了HSI局部平滑先验。此外该方法使用L p范数进行噪声建模,进一步增强对腐败的鲁棒性。该方法在两个数据集、七种加噪方式下与五种竞争方法在三个数值指标上进行了比较,结果充分反映了提出方法对复杂噪声场景的有效性和鲁棒性。展开更多
针对传统人脸识别算法在光照、遮挡和采样不足等情况下识别率低、运行速度慢的问题,提出一种基于lp范数(0< p <1)和融合字典的人脸识别算法。首先将训练样本矩阵分解,得到由类中心矩阵和类内变化矩阵组成的融合字典;然后利用lp范...针对传统人脸识别算法在光照、遮挡和采样不足等情况下识别率低、运行速度慢的问题,提出一种基于lp范数(0< p <1)和融合字典的人脸识别算法。首先将训练样本矩阵分解,得到由类中心矩阵和类内变化矩阵组成的融合字典;然后利用lp范数求解测试样本在融合字典下的稀疏表示。结果表明:该算法不仅鲁棒性强,识别率高,而且运行速度快。在Extended Yale B数据库上,与目前运行速度最快的基于lp范数(0<p <1)稀疏编码的人脸识别算法(SRC-p)相比,该算法的单张图像运行速度提高了1.39倍。展开更多
For 1≤ p 【 ∞, firstly we prove that for an arbitrary set of distinct nodes in [-1, 1], it is impossible that the errors of the Hermite-Fejr interpolation approximation in L p -norm are weakly equivalent to the corr...For 1≤ p 【 ∞, firstly we prove that for an arbitrary set of distinct nodes in [-1, 1], it is impossible that the errors of the Hermite-Fejr interpolation approximation in L p -norm are weakly equivalent to the corresponding errors of the best polynomial approximation for all continuous functions on [-1, 1]. Secondly, on the ground of probability theory, we discuss the p-average errors of Hermite-Fejr interpolation sequence based on the extended Chebyshev nodes of the second kind on the Wiener space. By our results we know that for 1≤ p 【 ∞ and 2≤ q 【 ∞, the p-average errors of Hermite-Fejr interpolation approximation sequence based on the extended Chebyshev nodes of the second kind are weakly equivalent to the p-average errors of the corresponding best polynomial approximation sequence for L q -norm approximation. In comparison with these results, we discuss the p-average errors of Hermite-Fejr interpolation approximation sequence based on the Chebyshev nodes of the second kind and the p-average errors of the well-known Bernstein polynomial approximation sequence on the Wiener space.展开更多
For a class of fractional-order linear continuous-time switched systems specified by an arbitrary switching sequence,the performance of PDα-type fractional-order iterative learning control(FOILC)is discussed in the s...For a class of fractional-order linear continuous-time switched systems specified by an arbitrary switching sequence,the performance of PDα-type fractional-order iterative learning control(FOILC)is discussed in the sense of L^p norm.When the systems are disturbed by bounded external noises,robustness of the PDα-type algorithm is firstly analyzed in the iteration domain by taking advantage of the generalized Young inequality of convolution integral.Then,convergence of the algorithm is discussed for the systems without any external noise.The results demonstrate that,under some given conditions,both convergence and robustness can be guaranteed during the entire time interval.Simulations support the correctness of the theory.展开更多
文摘在高光谱图像(HSI)恢复中,如何在模型中有效嵌入先验信息和正确建模噪声一直是研究的两个重点。边信息作为一种基于域的先验知识已经在许多方向取得了成功,然而在高光谱去噪领域仍未受到关注。为了将这种领域知识与高光谱恢复模型自然耦合,提出的方法采用双线性映射的方式将边信息链接到表示观测数据潜在低秩结构的底层矩阵,并使用E-3DTV(enhanced 3-D total variation)正则编码了HSI局部平滑先验。此外该方法使用L p范数进行噪声建模,进一步增强对腐败的鲁棒性。该方法在两个数据集、七种加噪方式下与五种竞争方法在三个数值指标上进行了比较,结果充分反映了提出方法对复杂噪声场景的有效性和鲁棒性。
基金supported by National Natural Science Foundation of China (Grant No.10471010)
文摘For 1≤ p 【 ∞, firstly we prove that for an arbitrary set of distinct nodes in [-1, 1], it is impossible that the errors of the Hermite-Fejr interpolation approximation in L p -norm are weakly equivalent to the corresponding errors of the best polynomial approximation for all continuous functions on [-1, 1]. Secondly, on the ground of probability theory, we discuss the p-average errors of Hermite-Fejr interpolation sequence based on the extended Chebyshev nodes of the second kind on the Wiener space. By our results we know that for 1≤ p 【 ∞ and 2≤ q 【 ∞, the p-average errors of Hermite-Fejr interpolation approximation sequence based on the extended Chebyshev nodes of the second kind are weakly equivalent to the p-average errors of the corresponding best polynomial approximation sequence for L q -norm approximation. In comparison with these results, we discuss the p-average errors of Hermite-Fejr interpolation approximation sequence based on the Chebyshev nodes of the second kind and the p-average errors of the well-known Bernstein polynomial approximation sequence on the Wiener space.
基金supported by the National Natural Science Foundation of China(61201323)the Special Fund Project for Promoting Scientific and Technological Innovation in Xuzhou City(KC18013)the Cultivation Project of Xuzhou Institute of Technology(XKY2017112)
文摘For a class of fractional-order linear continuous-time switched systems specified by an arbitrary switching sequence,the performance of PDα-type fractional-order iterative learning control(FOILC)is discussed in the sense of L^p norm.When the systems are disturbed by bounded external noises,robustness of the PDα-type algorithm is firstly analyzed in the iteration domain by taking advantage of the generalized Young inequality of convolution integral.Then,convergence of the algorithm is discussed for the systems without any external noise.The results demonstrate that,under some given conditions,both convergence and robustness can be guaranteed during the entire time interval.Simulations support the correctness of the theory.
