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Multilayer Perceptrons: Theory and Applications by Ruth Vang-Mata (English) Pape

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Last updated on 05 Jul, 2025 17:10:42 BSTView all revisionsView all revisions

Item specifics

Condition
New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN-13
9781536173642
Book Title
Multilayer Perceptrons
ISBN
9781536173642

About this product

Product Identifiers

Publisher
NOVA Science Publishers, Incorporated
ISBN-10
1536173649
ISBN-13
9781536173642
eBay Product ID (ePID)
6038395712

Product Key Features

Number of Pages
153 Pages
Language
English
Publication Name
Multilayer Perceptrons: Theory and Applications
Publication Year
2020
Subject
Computer Science, General
Type
Textbook
Author
Ruth Vang-Mata
Subject Area
Mathematics, Computers
Series
Computer Science, Technology and Applications Ser.
Format
Trade Paperback

Dimensions

Item Weight
8.6 Oz
Item Length
9 in
Item Width
6 in

Additional Product Features

LCCN
2020-001380
Illustrated
Yes
Table Of Content
Preface; Multilayer Perceptron Artificial Neural Network: A Review; Machine Learning Classification for Network Centric Therapy Utilizing the Multilayer Perceptron Neural Network; Age Estimation by Using Multi-Layer Perceptron Neural Network with Image Processing Techniques; Dynamic Forecasting of Electric Load Consumption Using Adaptive Multilayer Perceptron (AMLP); Development of the Pre-Fractal Pach Antenna with Artificial Neural Network; Index.
Synopsis
Multilayer Perceptrons: Theory and Applications opens with a review of research on the use of the multilayer perceptron artificial neural network method for solving ordinary/partial differential equations, accompanied by critical comments. A historical perspective on the evolution of the multilayer perceptron neural network is provided. Furthermore, the foundation for automated post-processing that is imperative for consolidating the signal data to a feature set is presented. In one study, panoramic dental x-ray images are used to estimate age and gender. These images were subjected to image pre-processing techniques to achieve better results. In a subsequent study, a multilayer perceptrons artificial neural network with one hidden layer and trained through the efficient resilient backpropagation algorithm is used for modeling quasi-fractal patch antennas. Later, the authors propose a scheme with eight steps for a dynamic time series forecasting using an adaptive multilayer perceptron with minimal complexity. Two different data sets from two different countries were used in the experiments to measure the robustness and accuracy of the models. In closing, a multilayer perceptron artificial neural network with a layer of hidden neurons is trained with the resilient backpropagation algorithm, and the network is used to model a Koch pre-fractal patch antenna., Multilayer Perceptrons: Theory and Applications opens with a review of research on the use of the multilayer perceptron artificial neural network method for solving ordinary/partial differential equations, accompanied by critical comments.A historical perspective on the evolution of the multilayer perceptron neural network is provided. Furthermore, the foundation for automated post-processing that is imperative for consolidating the signal data to a feature set is presented.In one study, panoramic dental x-ray images are used to estimate age and gender. These images were subjected to image pre-processing techniques to achieve better results. In a subsequent study, a multilayer perceptrons artificial neural network with one hidden layer and trained through the efficient resilient backpropagation algorithm is used for modeling quasi-fractal patch antennas.Later, the authors propose a scheme with eight steps for a dynamic time series forecasting using an adaptive multilayer perceptron with minimal complexity. Two different data sets from two different countries were used in the experiments to measure the robustness and accuracy of the models.In closing, a multilayer perceptron artificial neural network with a layer of hidden neurons is trained with the resilient backpropagation algorithm, and the network is used to model a Koch pre-fractal patch antenna.
LC Classification Number
QA76.87.M864 2020

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    Book arrived today, 2 days before deadline given by the seller. Well-packaged & in good condition. Price was very competitive, & the book was accurately listed. Great communication. I appreciate the seller getting back to me when I was having trouble tracking the book's delivery progress. Apparently there were 2 different tracking numbers - one in Canada & the other in the U.S., since it was initially shipped from Canada. Thank you very much for your quick response & helpful information.
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    Seller handles a massive inventory so I give them grace on the slow processing and shipping. They were very communicative and prompt with their response when I messaged in asking about it. Book was in good condition as described. Small ding on the page edges which wasn't mentioned, but that's fairly common even at your typical book store. Still a good value and I'd buy from them again.
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