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Quality recognition and prediction : smarter pattern technology with the Mahalanobis-Taguchi system

Author: Shoichi Teshima; Yoshiko Hasegawa; Kazuo Tatebayashi
Publisher: [New York, N.Y.] (222 East 46th Street, New York, NY 10017) : Momentum Press, 2012.
Series: The Momentum Press digital library
Edition/Format:   eBook : Document : English : 1st edView all editions and formats
Summary:
The MT system is a diagnostic and predictive method for analyzing patterns in multivariate data that has provided benefits in many diverse applications over the past decade or so. It has proven itself superior in many cases to more traditional artificial intelligence applications such as neural nets.
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Shoichi Teshima; Yoshiko Hasegawa; Kazuo Tatebayashi
ISBN: 9781606503447 1606503448
OCLC Number: 809681761
Description: 1 online resource (1 online resource (xvii, 220 pages)) : illustrations, digital file.
Contents: Foreword --
Preface --
Acknowledgments. 1. Pattern recognition and the MT system --
1.1 Overview of pattern recognition and the fields of application --
1.2 Standard execution procedure for pattern recognition --
1.3 Fields with substantial experience in the use of MT system applications. 2. Merits of the MT system and its computation methods --
2.1 Characteristics shared by all MT system components --
2.2 Features of the MT method --
2.3 Features of the T method --
2.4 The MT system computation formulas. 3. Data handled by the MT system and feature extraction --
3.1 Use of measured values in an unmodified form --
3.2 Performing feature extraction --
3.3 Feature extraction technique from character pattern --
3.4 Feature extraction technique from waveform pattern --
3.5 Differences between other waveform features and variation values/abundance values. 4. MT method application procedure and important points to heed --
4.1 Example of character recognition --
4.2 Example of weather prediction. 5. T method application procedures and key points --
5.1 Yield prediction for manufacturing-production using T method-1 --
5.2 Character pattern recognition using the RT method. 6. Examples of actual applications --
6.1 Blade wear monitoring via cutting vibration waveform (MT method) --
6.2 Appearance inspection of a clutch disk --
6.3 Monitoring of machine conditions (MT method) --
6.4 Application to medical diagnosis (MT method) --
6.5 Strength estimation based on raw material mixing (T method-1) --
6.6. Real estate price prediction by T method-1. Appendices --
A. Differences between the MT system and artificial intelligence --
B. Difference between the MT system and traditional statistical theory --
C. Supplementary considerations concerning mathematical formulas --
D. Strategy to use when data incorporates unmeasured values --
E. Fusion with artificial intelligence and other resources --
F. Mahalanobis distance computation using Microsoft Excel --
G. Paley's construct for generation of Hadamard matrice. Bibliography and reference sources --
Bibliography (in English) --
Bibliography (in Japanese) --
References --
Glossary: definition of terms --
Index --
About the authors.
Series Title: The Momentum Press digital library
Responsibility: Shoichi Teshima, Yoshiko Hasegawa, Kazuo Tatebayashi.

Abstract:

Offers a clear computational method to show the user how to actually apply the system to real manufacturing control problems. The book includes: an overview of pattern recognition issues and the  Read more...

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