title: Neural Net Gains Estimation Based on an Equivalent Model.
abstract: A model of an Equivalent Artificial Neural Net (EANN) describes the gains set, viewed as parameters in a layer, and this consideration is a reproducible process, applicable to a neuron in a neural net (NN). The EANN helps to estimate the NN gains or parameters, so we propose two methods to determine them. The first considers a fuzzy inference combined with the traditional Kalman filter, obtaining the equivalent model and estimating in a fuzzy sense the gains matrix A and the proper gain K into the traditional filter identification. The second develops a direct estimation in state space, describing an EANN using the expected value and the recursive description of the gains estimation. Finally, a comparison of both descriptions is performed; highlighting the analytical method describes the neural net coefficients in a direct form, whereas the other technique requires selecting into the Knowledge Base (KB) the factors based on the functional error and the reference signal built with the past information of the system.
authors.affiliation: Centro de Investigación en Computación, Instituto Politécnico Nacional (CIC-IPN), Avenida Juan de Dios Bátiz, Esq. Miguel Othón de Mendizábal, Col. Nueva Industrial Vallejo, Delegación Gustavo A. Madero, 07738 Ciudad de México, DF, Mexico.
authors.forename: Karen Alicia
authors.initials: KA
authors.lastname: Aguilar Cruz
authors.affiliation: Centro de Investigación en Computación, Instituto Politécnico Nacional (CIC-IPN), Avenida Juan de Dios Bátiz, Esq. Miguel Othón de Mendizábal, Col. Nueva Industrial Vallejo, Delegación Gustavo A. Madero, 07738 Ciudad de México, DF, Mexico.
authors.forename: José de Jesús
authors.initials: Jde J
authors.lastname: Medel Juárez
authors.affiliation: Centro de Investigación en Ciencia Aplicada y Tecnología Avanzada U. Legaria, Instituto Politécnico Nacional (CICATA-Legaria-IPN), Calzada Legaria 649, Col. Irrigación, Delegación Miguel Hidalgo, 11500 Ciudad de México, DF, Mexico.
authors.forename: José Luis
authors.initials: JL
authors.lastname: Fernández Muñoz
authors.affiliation: Centro de Investigación en Computación, Instituto Politécnico Nacional (CIC-IPN), Avenida Juan de Dios Bátiz, Esq. Miguel Othón de Mendizábal, Col. Nueva Industrial Vallejo, Delegación Gustavo A. Madero, 07738 Ciudad de México, DF, Mexico.
authors.forename: Midory
authors.initials: M
authors.lastname: Esmeralda Vigueras Velázquez
mesh_terms: D000465:Algorithms; D017143:Fuzzy Logic; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology*