Description: Feedforward Neural Network Methodology by Terrence L. Fine Estimated delivery 3-12 business days Format Paperback Condition Brand New Description The successful application of feedforward neural networks to time series forecasting has been multiply demonstrated and quite visibly so in the formation of market funds in which investment decisions are based largely on neural network–based forecasts of performance. Publisher Description The decade prior to publication has seen an explosive growth in com- tational speed and memory and a rapid enrichment in our understa- ing of arti?cial neural networks. These two factors have cooperated to at last provide systems engineers and statisticians with a working, prac- cal, and successful ability to routinely make accurate complex, nonlinear models of such ill-understood phenomena as physical, economic, social, and information-based time series and signals and of the patterns h- den in high-dimensional data. The models are based closely on the data itself and require only little prior understanding of the stochastic mec- nisms underlying these phenomena. Among these models, the feedforward neural networks, also called multilayer perceptrons, have lent themselves to the design of the widest range of successful forecasters, pattern clas- ?ers, controllers, and sensors. In a number of problems in optical character recognition and medical diagnostics, such systems provide state-of-the-art performance and such performance is also expected in speech recognition applications. The successful application of feedforward neural networks to time series forecasting has been multiply demonstrated and quite visibly so in the formation of market funds in which investment decisions are based largely on neural network–based forecasts of performance. The purpose of this monograph, accomplished by exposing the meth- ology driving these developments, is to enable you to engage in these - plications and, by being brought to several research frontiers, to advance the methodology itself. Details ISBN 1475773099 ISBN-13 9781475773095 Title Feedforward Neural Network Methodology Author Terrence L. Fine Format Paperback Year 2013 Pages 340 Publisher Springer-Verlag New York Inc. GE_Item_ID:143735366; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 67.04 USD
Location: Fairfield, Ohio
End Time: 2025-01-22T03:31:45.000Z
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Restocking Fee: No
Return shipping will be paid by: Buyer
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ISBN-13: 9781475773095
Book Title: Feedforward Neural Network Methodology
Number of Pages: Xvi, 340 Pages
Publication Name: Feedforward Neural Network Methodology
Language: English
Publisher: Springer New York
Item Height: 0.3 in
Publication Year: 2013
Subject: Probability & Statistics / General, Intelligence (Ai) & Semantics, Neural Networks, Physics / Mathematical & Computational
Type: Textbook
Item Weight: 19.4 Oz
Subject Area: Mathematics, Computers, Science
Author: Terrence L. Fine
Item Length: 9.3 in
Item Width: 6.1 in
Series: Information Science and Statistics Ser.
Format: Trade Paperback
