title: [Extended Kalman filtering trained neural networks and multicomponent analysis of amino acids].
abstract: The principle of neural networks was briefly described. Backpropagation (BP) is a widely used algorithm to train NN with slow convergence and local optima. In order to overcome the above weakness of BP, a novel learning algorithm, extanded Kalman filtering (EKF, EF), was proposed with high performance. EFNN was used for simultaneous multi-component analysis with good results and no separation.
authors.affiliation: Hunan University, Changsha, 410082 Changsha.
authors.forename: Z
authors.initials: Z
authors.lastname: Li
authors.forename: S
authors.initials: S
authors.lastname: Matsumoto
authors.forename: B
authors.initials: B
authors.lastname: Yu
authors.forename: M
authors.initials: M
authors.lastname: Sakai
authors.forename: M L
authors.initials: ML
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000032:analysis*; D016571:Neural Networks, Computer; D013056:Spectrophotometry, Ultraviolet
chemical_list: D000596:Amino Acids