人工智慧：智慧型系統導論 (3版)

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書名：人工智慧：智慧型系統導論(第三版) 作者：李聯旺 出版社：全華 ISBN：9789862800959

機器學習：類神經網路、模糊系統以及基因演算法則 (4版)

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書名：機器學習：類神經網路、模糊系統以及基因演算法則(第四版) 作者：蘇木春、張孝德 出版社：全華 出版日期：2016/05/00 ISBN：9789864632060 內容簡介 ■ 本書優點特色 1.將三種與機械學習相關的技術-類神經網路、模糊系統及基因演繹法作一通盤介紹。 2.以深入淺出的方式建立類神經網路與生物神經網路的關聯性，以便讓讀者更能發揮想像力。 3.每一種理論都儘可能配合書中範例及圖表加以說明。 ■ 內容簡介 本書將三種與機械學習相關的技術-類神經網路、模糊系統及基因演繹法作一通盤介紹。此外，作者以深入淺出的方式建立類神經網路與生物神經網路的關聯性，以便讓讀者更能發揮想像力。 目錄 第1章 類神經網路之簡介 第2章 感知機 第3章 多層感知機 第4章 非監督式類神經網路 第5章 聯想記憶 第6章 增強式學習 第7章 模糊集合 第8章 模糊關係及推論 第9章 模糊系統 第10章 基因演算法則

Matrix Pathobiology and Angiogenesis (1版)

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In the vasculature, the extracellular matrix (ECM) is involved in the regulation of angiogenesis, vascular mechanosensing, and blood vessel stability. This book aims to provide the reader with an overview of the various roles of the ECM during angiogenesis and covers its important role for the maintenance of vascular integrity, capillary and arterial morphogenesis, as well as lymphangiogenesis. Furthermore, aspects of regulation of endothelial cell and pericyte functions by the ECM under physiological and pathological conditions are discussed. In addition, the reader will learn more about different approaches to exploit ECM molecules for designing therapeutic approaches or as biomarkers to improve therapeutic decisions. Comprehensive and cutting-edge, Matrix Pathobiology and Angiogenesis is a valuable resource for experienced researchers and early career scientist alike, who are interested in in learning more about this exciting and developing field. The series Biology of Extracellular Matrix is published in collaboration with the American Society for Matrix Biology and the International Society for Matrix Biology.

Quantum Geometry, Matrix Theory, and Gravity (1版)

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【簡介】 Building on mathematical structures familiar from quantum mechanics, this book provides an introduction to quantization in a broad context before developing a framework for quantum geometry in Matrix Theory and string theory. Taking a physics-oriented approach to quantum geometry, this framework helps explain the physics of Yang–Mills-type matrix models, leading to a quantum theory of space-time and matter. This novel framework is then applied to Matrix Theory, which is defined through distinguished maximally supersymmetric matrix models related to string theory. A mechanism for gravity is discussed in depth, which emerges as a quantum effect on quantum space-time within Matrix Theory. Using explicit examples and exercises, readers will develop a physical intuition for the mathematical concepts and mechanisms. It will benefit advanced students and researchers in theoretical and mathematical physics, and is a useful resource for physicists and mathematicians interested in the geometrical aspects of quantization in a broader context. 【目錄】 Preface The trouble with spacetime Quantum geometry and Matrix theory Part I. Mathematical Background: 1. Differentiable manifolds 2. Lie groups and coadjoint orbits Part II. Quantum Spaces and Geometry: 3. Quantization of symplectic manifolds 4. Quantum spaces and matrix geometry 5. Covariant quantum spaces Part III. Noncommutative field theory and matrix models: 6. Noncommutative field theory 7. Yang–Mills matrix models and quantum spaces 8. Fuzzy extra dimensions 9. Geometry and dynamics in Yang–Mills matrix models 10. Higher-spin gauge theory on quantum spacetime Part IV. Matrix Theory and Gravity: 11. Matrix theory: maximally supersymmetric matrix models 12. Gravity as a quantum effect on quantum spacetime 13. Matrix quantum mechanics and the BFSS model Appendixes References Index.

Introduction to Matrix Theory (2版)

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Linear algebra and matrix theory are among the most important and most frequently applied branches of mathematics. They are especially important in solving engineering and economic models, where either the model is assumed linear, or the nonlinear model is approximated by a linear model, and the resulting linear model is examined. This book is mainly a textbook, that covers a one semester upper division course or a two semester lower division course on the subject. The second edition will be an extended and modernized version of the first edition. We added some new theoretical topics and some new applications from fields other than economics. We also added more difficult exercises at the end of each chapter which require deep understanding of the theoretical issues. We also modernized some proofs in the theoretical discussions which give better overview of the study material. In preparing the manuscript we also corrected the typos and errors, so the second edition will be a corrected, extended and modernized new version of the first edition. Request Inspection Copy Sample Chapter(s) Preface Chapter 1: Vectors and Matrices Contents: Vectors and Matrices Vector Spaces and Inner-Product Spaces Systems of Linear Equations, and Inverses of Matrices Determinants Linear Mappings and Matrices Eigenvalues, Invariant Subspaces, Canonical Forms Special Matrices Elements of Matrix Analysis Readership: Written primarily for undergraduate and graduate students studying engineering, economics and business; can also be used in courses offered by the mathematics department, or by any kind of engineering and social sciences; can also be used by researchers in mathematics, economics, engineering; in addition, high school special courses, and teacher training courses can employ this textbook.

Matrix and Tensor Decompositions in Signal Processing, Volume 2

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The second volume will deal with a presentation of the main matrix and tensor decompositions and their properties of uniqueness, as well as very useful tensor networks for the analysis of massive data. Parametric estimation algorithms will be presented for the identification of the main tensor decompositions. After a brief historical review of the compressed sampling methods, an overview of the main methods of retrieving matrices and tensors with missing data will be performed under the low rank hypothesis. Illustrative examples will be provided.