隋方功, 李俊良. 土壤农化分析实验[M]. 北京:中国农业大学出版社, 2004. SUI F G, LI J L. Agrochemical Soil Analysis Experiment [M]. Beijing:China Agriculture Press, 2004. (in Chinese)

陆婉珍. 现代近红外光谱分析技术[M]. 2版. 北京:中国石化出版社, 2007. LU W Z. Modern Near Infrared Spectroscopy Analyticat Technology [M]. 2nd ed. Beijing:China Petrochemical Press, 2007. (in Chinese)

褚小立, 陆婉珍. 近五年我国近红外光谱分析技术研究与应用进展[J]. 光谱学与光谱分析, 2014, 34(10):2595-2605. CHU X L, LU W Z. Research and application progress of near infrared spectroscopy analytical technology in China in the past five years[J]. Spectrosc. Spect. Anal., 2014, 34(10):2595-2605. (in Chinese)

HE Y, HUANG M, GARCA A, et al.. Prediction of soil macronutrients content using near-infrared spectroscopy[J]. Comput. Electron. Agric., 2007, 58(2):144-153.

鲍一丹, 何勇, 方慧, 等. 土壤的光谱特征及氮含量的预测研究[J]. 光谱学与光谱分析, 2001, 27(1):62-65. BAO Y D, HE Y, FANG H, et al.. Spectral characterization and N content prediction of soil with different particle size and moisture content[J]. Spectrosc. Spect. Anal., 2001, 27(1):62-65. (in Chinese)

朱登胜, 吴迪, 宋海燕, 等. 应用近红外光谱法测定土壤的有机质和pH值[J]. 农业工程学报, 2008, 24(6):196-199. ZHU D S, WU D, SONG H Y, et al.. Determination of organic matter contents and pH values of soil using near infrared spectroscopy[J]. Trans. CSAE, 2008, 24(6):196-199. (in Chinese)

李伟, 张书慧, 张倩, 等. 近红外光谱法快速测定土壤碱解氮、速效磷和速效钾含量[J]. 农业工程学报, 2007, 23(1):55-59. LI W, ZHANG S H, ZHANG Q, et al.. Rapid prediction of available N, P and K content in soil using near-infrared reflectance spectroscopy[J]. Trans. CSAE, 2007, 23(1):55-59. (in Chinese)

MOUAZEN A M, KUANG B, DE BAERDEMAEKER J, et al.. Comparison among principal component, partial least squares and back propagation neural network analyses for accuracy of measurement of selected soil properties with visible and near infrared spectroscopy[J]. Geoderma, 2010, 158(1-2):23-31.

许禄, 邵学广. 化学计量学方法[M]. 2版. 北京:科学出版社, 2004. XU L, SHAO X G. Chemometric Methods [M]. 2nd ed. Beijing:Science Press, 2004. (in Chinese)

褚小立. 化学计量学方法与分子光谱分析技术[M]. 北京:化学工业出版社, 2011. CHU X L. Molecular Spectroscopy Analytical Technology Combined with Chemometrics and its Applications [M]. Beijing:Chemical Industry Press, 2011. (in Chinese)

蒋宗礼. 人工神经网络导论[M]. 北京:高等教育出版社, 2001:8. JIANG Z L. Introduction to Aritificial Neural Networks [M]. Beijing:Higher Education Press, 2001:8. (in Chinese)

HAYKIN S. 神经网络与机器学习[M]. 申富饶, 徐烨, 郑俊, 等, 译. 3版. 北京:机械工业出版社, 2011:3. HAYKIN S. Neural Networks and Learning Machines [M]. SHEN F R, XU Y, ZHENG J, et al.. Trans. 3rd ed. Beijing:Mechanical Industry Press, 2011:3. (in Chinese)

牛晓颖, 邵利敏, 赵志磊, 等. 基于BP-ANN的草莓品种近红外光谱无损鉴别方法研究[J]. 光谱学与光谱分析, 2012, 32(8):2095-2099. NIU X Y, SHAO L M, ZHAO Z L, et al.. Nondestructive discrimination of strawberry varieties by NIR and BP-ANN[J]. Spectrosc. Spect. Anal., 2012, 32(8):2095-2099. (in Chinese)

QU Z H, WANG L H. Prediction of lignin content of manchurian walnut by BP neural network and near-infrared spectroscopy[J]. Adv. Mater. Res., 2011, 267:991-994.

郑立华, 李民赞, 潘娈, 等. 基于近红外光谱技术的土壤参数BP神经网络预测[J]. 光谱学与光谱分析, 2008, 28(5):1160-1164. ZHENG L H, LI M Z, PAN L, et al.. Estimation of soil organic matter and soil total nitrogen based on NIR spectroscopy and BP neural network[J]. Spectrosc. Spect. Anal., 2008, 28(5):1160-1164. (in Chinese)

VESANTO J, ALHONIEMI E. Clustering of the self-organizing map[J]. IEEE Trans. Neural Netw., 2000, 11(3):586-600.

KOHONEN T. Essentials of the self-organizing map[J]. Neural Netw., 2013, 37:52-65.

CRPUT J C, HAJJAM A, KOUKAM A, et al.. Self-organizing maps in population based metaheuristic to the dynamic vehicle routing problem[J]. J. Comb. Optim., 2012, 24(4):437-458.

BALLABIO D, VASIGHI M. A MATLAB toolbox for self organizing maps and supervised neural network learning strategies[J]. Chemom. Intell. Lab. Syst., 2012, 118:24-32.

HUANG G B, SARATCHANDRAN P, SUNDARARAJAN N. A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation[J]. IEEE Trans. Neural Netw., 2005, 16(1):57-67.

MELAGRAKI G, AFANTITIS A, MAKRIDIMA K, et al.. Prediction of toxicity using a novel RBF neural network training methodology[J]. J. Mol. Model., 2006, 12(3):297-305.

MELAGRAKI G, AFANTITIS A, MAKRIDIMA K, et al.. Prediction of toxicity using a novel RBF neural network training methodology[J]. J. Mol. Model., 2006, 12(3):297-305.

HINTON G E, SALAKHUTDINOV R R. Reducing the dimensionality of data with neural networks[J]. Science, 2006, 313(5786):504-507.

余凯, 贾磊, 陈雨强, 等. 深度学习的昨天、今天和明天[J]. 计算机研究与发展, 2013, 50(9):1799-1804. YU K, JIA L, CHEN Y Q, et al.. Deep learning:yesterday, today, and tomorrow[J]. J. Comput. Res. Dev., 2013, 50(9):1799-1804. (in Chinese)

刘建伟, 刘媛, 罗雄麟. 深度学习研究进展[J]. 计算机应用研究, 2014, 31(7):1921-1930. LIU J W, LIU Y, LUO X L. Research and development on deep learning[J]. Appl. Comput. Res., 2014, 31(7):1921-1930. (in Chinese)

DONOHO D L. Compressed sensing[J]. IEEE Trans. Inf. Theory, 2006, 52(4):1289-1306.

ZHANG C M, YIN Z K, CHEN X D, et al.. Signal overcomplete representation and sparse decomposition based on redundant dictionaries[J]. Chin. Sci. Bull., 2005, 50(23):2672-2677.

AHARON M, ELAD M, BRUCKSTEIN A. rmK-SVD:an algorithm for designing overcomplete dictionaries for sparse representation[J]. IEEE Trans. Signal Process., 2006, 54(11):4311-4322.