Edward J. Rzempoluck

Neural Network Data Analysis Using Simulnet(TM) (eBook, PDF)

• Format: PDF

Produktbeschreibung

This book and sofwtare package provide a complement to the traditional data analysis tools already widely available. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: these include neural networks, genetic algorithms, probabilistic networks. The text presents a number of worked examples and case studies using Simulnet, the software package which comes with the book.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Springer US
• Seitenzahl: 226
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461217466
• Artikelnr.: 44045360

Inhaltsangabe

Scope of this Text.- What Is Expected from the Reader.- An Outline.- Computer Requirements.- 1 The Simulnet Desktop.- Desktop Components.- 2 Data Analysis.- The Substantive Question.- Neural Network Analysis.- Genetic Algorithms and Neural Networks.- The Probabilistic Network.- The Vector Quantizer Network.- Assessing the Significance of Network Results.- Network Application Examples.- Fractal Dimension Analysis.- Fourier Analysis.- Eigenvalue Analysis.- Coherence and Phase Analysis.- Mutual Information Analysis.- Correlation and Covariance Analysis.- 3 Acquiring and Conditioning Network Data.- Data Specification.- Data Collection.- Data Inspection.- Data Conditioning.- Detrend-Order 0.- Standardize Columns.- Frequency Filtering.- Principal Component Analysis.- Principal Component Data Reduction.- 4 A Data Analysis Protocol.- A Preprocessing Checklist.- Analyzing Experimental Data.