Pattern Recognition, Fourth Edition
Pattern Recognition, Fourth Edition
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发表时间：
2008-09
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通讯作者：
S. Theodoridis;K. Koutroumbas
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作者：
S. Theodoridis;K. Koutroumbas
本书考虑了监督和无监督模式识别的经典和当前理论与实践，为工程专业人士和学生构建了完整的背景。作者是模式识别领域的顶尖专家，他们提供了一本最新的、独立的卷，其中包含了广泛的信息。此版本包含了最新的方法：半监督学习、结合聚类算法和相关性反馈。此版本包含更多工作示例和图表（两种颜色），以帮助更好地理解这些方法及其应用。基于计算机的问题将包含在 MATLAB 代码中。随附的书包含额外的工作示例和本书中使用的所有示例的 MATLAB 代码。经过彻底开发，包括更多的工作示例，以更好地理解这个以数学为导向的主题。包含更多图表（现在有两种颜色），通过视觉演示提供更深入的了解。随附的手册包括书中方法和算法的 Matlab 代码，以及医学成像、遥感和音频识别中已解决的问题和现实数据集。该手册可单独购买，也可按特价打包购买（ISBN：9780123744869）。包含半监督学习、组合聚类算法和相关性反馈等最新热点主题，进一步提高文本的参考价值。
This book considers classical and current theory and practice, of both supervised and unsupervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the field of pattern recognition, have provided an up-to-date, self-contained volume encapsulating this wide spectrum of information. The very latest methods are incorporated in this edition: semi-supervised learning, combining clustering algorithms, and relevance feedback.This edition includes many more worked examples and diagrams (in two colour) to help give greater understanding of the methods and their application. Computer-based problems will be included with MATLAB code. An accompanying book contains extra worked examples and MATLAB code of all the examples used in this book.Thoroughly developed to include many more worked examples to give greater understanding of this mathematically oriented subjectMany more diagrams included--now in two color--to provide greater insight through visual presentationAn accompanying manual includes Matlab code of the methods and algorithms in the book, together with solved problems and real-life data sets in medical imaging, remote sensing and audio recognition. The Manual is available separately or at a special packaged price (ISBN: 9780123744869).Latest hot topics included to further the reference value of the text including semi-supervised learning, combining clustering algorithms, and relevance feedback.