[1] |
Zhang P. Research of digital construction of Paper files and relics [J]. Cultural Relics of Central Plains, 2009(5):104-107.
|
[2] |
Lv X Q, Li M N et al. An oracle classification method based on figure recognition [J]. Journal of Beijing University of Information Science and Technology, 2010(25):92-96.
|
[3] |
Chen D, Li N, Li L. Online handwriting recognition research of ancient character[J]. Journal of Beijing Institute of Mechanical Industry, 2008(4):32-37.
|
[4] |
Zang G Q. Experiment and Improvement of accuracy of OCR for text-digital image [J]. Intelligence, Information and Sharing, 2010(3):62-67.
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[5] |
Vapnik V. The Nature of Statistical Learning Theory[M]. New York: Springer-Verlag, 1995.
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[6] |
Suykens J A K, Vandewalle J. Least Squares Support Vector Machine Classifiers[J]. Neural Process Letters, 1999 (3):293-300.
|
[7] |
Miranian A, Abdollahzade M. Developing a Local Least-Squares Support Vector Machines-Based Neuro-Fuzzy Model for Nonlinear and Chaotic Time Series Prediction[J]. IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(2): 207-218.
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[8] |
Wang L G , Liu D F , Wang Q M et al. Spectral Unmixing Model Based on Least Squares Support Vector Machine With Unmixing Residue Constraints[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(6): 1592-1596.
|
[9] |
Liu B Y, Yang R G. A novel method based on PCA and LS-SVM for power load forecasting[C]. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, NanJing, 2008: 759-763.
|
[10] |
Zhang H R, Wang X D, Zhang C J et al. Soft sensor technique using LS-SVM and standard SVM[J]. IEEE International Conference on Information Acquisition, Hong Kong and Macau, 2005: 124-127.
|
[11] |
Xie J H. Printed character recognition using Kernel CCA with LS-SVM method[C]. Computer and Automation Engineering, 2010: 284-287.
|
[12] |
Yin D Y, Wu Y Q. Detection of Small Target in Infrared Image Based on KFCM and LS-SVM[C].International Conference on Intelligent Human-Machine Systems and Cybernetics, 2010: 309-312.
|
[13] |
Suykens J A K, de Brabanter J, Lukas L, Vandeewalle J. Weighted Least squares support vector machines: robustness and sparse approximation[J]. Neurocomputing, 2002(48):85-105.
|
[14] |
Smits G F, Jordaan E M. Improved SVM regression using mixtures of kernels[C]. textitin Neural Networks, International Joint Conference on, 2002, 3: 2785-2790.
|
[15] |
温昌兵. 基于特征融合的脱机手写体汉字识别[D]. 北京,北京科技大学,2005.
|
[16] |
Zhang X B, Huang H, Zhang S J. A FCM clustering algorithm based on Semi-supervised and Point Density Weighted[C]. Intelligent Computing and Intelligent Systems, 2010: 710-713.
|
[17] |
Tu Y K, Chen Q H, Huang L. Handwritten Chinese character recognition based on pseudo two-dimensional elastic mesh [J]. Journal of Huazhong University of Science and Technology, 2010(38):38-40.
|
[1] |
Zhang P. Research of digital construction of Paper files and relics [J]. Cultural Relics of Central Plains, 2009(5):104-107.
|
[2] |
Lv X Q, Li M N et al. An oracle classification method based on figure recognition [J]. Journal of Beijing University of Information Science and Technology, 2010(25):92-96.
|
[3] |
Chen D, Li N, Li L. Online handwriting recognition research of ancient character[J]. Journal of Beijing Institute of Mechanical Industry, 2008(4):32-37.
|
[4] |
Zang G Q. Experiment and Improvement of accuracy of OCR for text-digital image [J]. Intelligence, Information and Sharing, 2010(3):62-67.
|
[5] |
Vapnik V. The Nature of Statistical Learning Theory[M]. New York: Springer-Verlag, 1995.
|
[6] |
Suykens J A K, Vandewalle J. Least Squares Support Vector Machine Classifiers[J]. Neural Process Letters, 1999 (3):293-300.
|
[7] |
Miranian A, Abdollahzade M. Developing a Local Least-Squares Support Vector Machines-Based Neuro-Fuzzy Model for Nonlinear and Chaotic Time Series Prediction[J]. IEEE Transactions on Neural Networks and Learning Systems, 2013, 24(2): 207-218.
|
[8] |
Wang L G , Liu D F , Wang Q M et al. Spectral Unmixing Model Based on Least Squares Support Vector Machine With Unmixing Residue Constraints[J]. IEEE Geoscience and Remote Sensing Letters, 2013, 10(6): 1592-1596.
|
[9] |
Liu B Y, Yang R G. A novel method based on PCA and LS-SVM for power load forecasting[C]. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, NanJing, 2008: 759-763.
|
[10] |
Zhang H R, Wang X D, Zhang C J et al. Soft sensor technique using LS-SVM and standard SVM[J]. IEEE International Conference on Information Acquisition, Hong Kong and Macau, 2005: 124-127.
|
[11] |
Xie J H. Printed character recognition using Kernel CCA with LS-SVM method[C]. Computer and Automation Engineering, 2010: 284-287.
|
[12] |
Yin D Y, Wu Y Q. Detection of Small Target in Infrared Image Based on KFCM and LS-SVM[C].International Conference on Intelligent Human-Machine Systems and Cybernetics, 2010: 309-312.
|
[13] |
Suykens J A K, de Brabanter J, Lukas L, Vandeewalle J. Weighted Least squares support vector machines: robustness and sparse approximation[J]. Neurocomputing, 2002(48):85-105.
|
[14] |
Smits G F, Jordaan E M. Improved SVM regression using mixtures of kernels[C]. textitin Neural Networks, International Joint Conference on, 2002, 3: 2785-2790.
|
[15] |
温昌兵. 基于特征融合的脱机手写体汉字识别[D]. 北京,北京科技大学,2005.
|
[16] |
Zhang X B, Huang H, Zhang S J. A FCM clustering algorithm based on Semi-supervised and Point Density Weighted[C]. Intelligent Computing and Intelligent Systems, 2010: 710-713.
|
[17] |
Tu Y K, Chen Q H, Huang L. Handwritten Chinese character recognition based on pseudo two-dimensional elastic mesh [J]. Journal of Huazhong University of Science and Technology, 2010(38):38-40.
|