Description: New Backpropagation Algorithm With Type-2 Fuzzy Weights for Neural Networks, Paperback by Gaxiola, Fernando; Melin, Patricia; Valdez, Fevrier, ISBN 3319340867, ISBN-13 9783319340869, Brand New, Free shipping in the US In this book a neural network learning method with type-2 fuzzy weight adjustment is proposed. The mathematical analysis of the proposed learning method architecture and the adaptation of type-2 fuzzy weights are presented. The proposed method is based on research of recent methods that handle weight adaptation and especially fuzzy weights.The internal operation of the neuron is changed to work with two internal calculations for the activation function to obtain two results as outputs of the proposed method. Simulation results and a comparative study among monolithic neural networks, neural network with type-1 fuzzy weights and neural network with type-2 fuzzy weights are presented to illustrate the advantages of the proposed method.The proposed approach is based on recent methods that handle adaptation of weights using fuzzy logic of type-1 and type-2. The proposed approach is applied to a cases of prediction for the Mackey-Glass (for รด=17) and Dow-Jones time series, and recognition of person with iris biometric measure. In some experiments, noise was applied in different levels to the test data of the Mackey-Glass time series for showing that the type-2 fuzzy backpropagation approach obtains better behavior and tolerance to noise than the other methods.The optimization algorithms that were used are the genetic algorithm and the particle swarm optimization algorithm and the purpose of applying these methods was to find the optimal type-2 fuzzy inference systems for the neural network with type-2 fuzzy weights that permit to obtain the lowest prediction error.
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Book Title: New Backpropagation Algorithm With Type-2 Fuzzy Weights for Neura
Number of Pages: IX, 102 Pages
Publication Name: New Backpropagation Algorithm with Type-2 Fuzzy Weights for Neural Networks
Language: English
Publisher: Springer International Publishing A&G
Item Height: 0.2 in
Subject: Engineering (General), Intelligence (Ai) & Semantics, Neural Networks, Algebra / General, Optimization
Publication Year: 2016
Type: Textbook
Item Weight: 64.4 Oz
Item Length: 9.2 in
Author: Fevrier Valdez, Patricia Melin, Fernando Gaxiola
Subject Area: Computers, Technology & Engineering, Mathematics
Item Width: 6.1 in
Series: Springerbriefs in Applied Sciences and Technology Ser.
Format: Trade Paperback
