Algorithms to Live By.Algorithms to Live By.Algorithms to Live By.

Convex Optimization Algorithms原版电子版，凸优化经典教材 Dimitri P. Bertsekas Massachusetts Institute of Technology

@book{book:1351405, title = {Quantum Algorithms via Linear Algebra: A Primer}, author = {Richard J. Lipton, Kenneth W. Regan}, publisher = {The MIT Press}, isbn = {0262028395,9780262028394}, year = {2014}, }

盲源分离，语音增强 Blind source separation (BSS) methods have received extensive attention over the past two decades; thanks to its wide applicability in a number of areas such as biomedical engineering, audio signal processing, and telecommunications. The problem of source separation is an inductive inference problem, as only limited information, e.g., the sensor observations, is available to infer the most probable source estimates.

Ideal for graduate and senior undergraduate courses in computer arithmetic and advanced digital design, Computer Arithmetic: Algorithms and Hardware Designs, Second Edition, provides a balanced, comprehensive treatment of computer arithmetic. It covers topics in arithmetic unit design and circuit implementation that complement the architectural and algorithmic speedup techniques used in high-performance computer architecture and parallel processing. Using a unified and consistent framework, the text begins with number representation and proceeds through basic arithmetic operations, floating-point arithmetic, and function evaluation methods. Later chapters cover broad design and implementation topics-including techniques for high-throughput, low-power, fault-tolerant, and reconfigurable arithmetic. An appendix provides a historical view of the field and speculates on its future. An indispensable resource for instruction, professional development, and research, Computer Arithmetic: Algorithms and Hardware Designs, Second Edition, combines broad coverage of the underlying theories of computer arithmetic with numerous examples of practical designs, worked-out examples, and a large collection of meaningful problems. This second edition includes a new chapter on reconfigurable arithmetic, in order to address the fact that arithmetic functions are increasingly being implemented on field-programmable gate arrays (FPGAs) and FPGA-like configurable devices. Updated and thoroughly revised, the book offers new and expanded coverage of saturating adders and multipliers, truncated multipliers, fused multiply-add units, overlapped quotient digit selection, bipartite and multipartite tables, reversible logic, dot notation, modular arithmetic, Montgomery modular reduction, division by constants, IEEE floating-point standard formats, and interval arithmetic. Features: * Divided into 28 lecture-size chapters * Emphasizes both the underlying theories of computer arithmetic and actua

Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them. Table of Contents Chapter 1. Introduction to algorithms Chapter 2. Selection sort Chapter 3. Recursion Chapter 4. Quicksort Chapter 5. Hash tables Chapter 6. Breadth-first search Chapter 7. Dijkstra’s algorithm Chapter 8. Greedy algorithms Chapter 9. Dynamic programming Chapter 10. K-nearest neighbors

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills. The book covers a wide range of topics―from numerical linear algebra to optimization and differential equations―focusing on real-world motivation and unifying themes. It incorporates cases from computer science research and practice, accompanied by highlights from in-depth literature on each subtopic. Comprehensive end-of-chapter exercises encourage critical thinking and build students’ intuition while introducing extensions of the basic material. The text is designed for advanced undergraduate and beginning graduate students in computer science and related fields with experience in calculus and linear algebra. For students with a background in discrete mathematics, the book includes some reminders of relevant continuous mathematical background. Table of Contents Section I: Preliminaries Chapter 1: Mathematics Review Chapter 2: Numerics and Error Analysis Section II: Linear Algebra Chapter 3: Linear Systems and the LU Decomposition Chapter 4: Designing and Analyzing Linear Systems Chapter 5: Column Spaces and QR Chapter 6: Eigenvectors Chapter 7: Singular Value Decomposition Section III: Nonlinear Techniques Chapter 8: Nonlinear Systems Chapter 9: Unconstrained Optimization Chapter 10: Constrained Optimization Chapter 11: Iterative Linear Solvers Chapter 12: Specialized Optimization Methods Section IV: Functions, Derivatives, and Integrals Chapter 13: Interpolation Chapter 14: Integration and Differentiation Chapter 15: Ordinary Differential Equations Chapter 16: Partial Differential Equations

Data Structures and Algorithms in Java 6th Edition.2014 教程及Solution Manual

Two Dimensional Phase Unwrapping Theory Algorithms and Software，扫描文档，清晰度一般。

分布式计算经典书籍Distributed computing-principles, algorithms, and systems(英文原版)（英文原版），pdf格式