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入門MTシステム

【主要内容】
MTシステムは、パターン認識や予測のための新しい手法です。ニューラルネットワークあるいは回帰分析などとは異なる考え方や数理を使用し、パターンの違いや程度を適切に定量化します。ものづくりや医療・経済などの現場で、有用な情報を獲得することができ、品質工学(タグチメソッド)の中でもいっそうの活用が期待されています。本書は、MTシステムの考え方や使い方を、基礎から体系的に理解できるように解説しています。豊富な事例、Excelによる計算方法や専用の計算ソフトも紹介しています。多様で膨大なデータを前に一瞬立ち止まっている方々、認識・予測について勉強したいと考えている方々にお勧めします。


【主要目次】
         第1章 パターン認識とMTシステム
         第2章 MTシステムの体系と各計算法の特徴
         第3章 MTシステムで取り扱うデータと特徴抽出
         第4章 MT法の適用手順とポイント
         第5章 T法の適用手順とポイント
         第6章 適用事例
         第7章 MTシステムの課題と期待される展開
         第8章 そのほかの話題




Quality Recognition and Prediction
-Smarter Pattern Technology with the Mahalanobis-Taguchi System

Abstract
The Mahalanobis-Taguchi (MT) System is a new theory for pattern recognition and prediction. It is based on concepts and principles from the neural network, or regression analysis, approaches--taking differences in patterns and the degrees of such differences and then adequately quantifying them. Using the MT System in fields such as manufacturing, medical treatment, and economics, it is now possible to acquire a broader and more accurate range of information than previous methods were able to supply. This new book builds on the success of the authors' previous Japanese-language book, An Introduction to the MT System, to meet the needs of a worldwide readership. For people who have been heretofore overwhelmed by massive quantities of data, as well as those who wish to study effective recognition and prediction methodology, this breakthrough book offers: * A concise explanation of the concepts behind the MT System and its various uses. * An introduction to the necessary computational methods for putting the MT System into practice. * Abundant case studies on how to manage and use data with the MT System and extract useful information conclusions. * A clearer understanding of the advantages and disadvantages between traditional Artificial Intelligence systems and the MT system.


Contents
Chapter1 PATTERN RECOGNITION AND THE MT SYSTEM 1
Chapter2 MERITS OF THE MT SYSTEM AND ITS COMPUTATION METHODS 15
Chapter3 DATA HANDLED BY THE MT SYSTEM AND FEATURE EXTRACTION 55
Chapter4 MT METHOD APPLICATION PROCEDURE AND IMPORTANT POINTS TO HEED
Chapter5 T METHOD APPLICATION PROCEDURES AND KEY POINTS 87
Chapter6 EXAMPLES OF ACTUAL APPLICATIONS 123


APPENDICES
  A DIFFERENCES BETWEEN THE MT SYSTEM AND ARTIFICIAL INTELLIGENCE 169
  B DIFFERENCE BETWEEN THE MT SYSTEM AND TRADITIONAL STATISTICAL
  C SUPPLEMENTARY CONSIDERATIONS CONCERNING MATHEMATICAL FORMULAS 183
  D STRATEGY TO USE WHEN DATA INCORPORATES UNMEASURED VALUES 185
  E FUSION WITH ARTIFICIAL INTELLIGENCE AND OTHER RESOURCES 187
  F MAHALANOBIS DISTANCE COMPUTATION USING MICROSOFT EXCEL 191
  G PALEY’S CONSTRUCT FOR GENERATION OF HADAMARD MATRICE 201

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