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Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

  • Stochastic Stability and Control

    • 1st Edition
    • Volume 33
    • Kushner
    • English
  • Advances in Computers

    • 1st Edition
    • Volume 8
    • English
  • Optimization of Stochastic Systems

    Topics in Discrete-time Systems
    • 1st Edition
    • Volume 32
    • Masanao Aoki
    • English
    Optimization of Stochastic Systems is an outgrowth of class notes of a graduate level seminar on optimization of stochastic systems. Most of the material in the book was taught for the first time during the 1965 Spring Semester while the author was visiting the Department of Electrical Engineering, University of California, Berkeley. The revised and expanded material was presented at the Department of Engineering, University of California, Los Angeles during the 1965 Fall Semester. The systems discussed in the book are mostly assumed to be of discrete-time type with continuous state variables taking values in some subsets of Euclidean spaces. There is another class of systems in which state variables are assumed to take on at most a denumerable number of values, i.e., these systems are of discrete-time discrete-space type. Although the problems associated with the latter class of systems are many and interesting, andalthough they are amenable to deep analysis on such topics as the limiting behaviors of state variables as time indexes increase to infinity, this class of systems is not included here, partly because there are many excellent books on the subjects and partly because inclusion of these materials would easily double the size of the book.
  • Introduction to the Mathematical Theory of Control Processes: Linear Equations and Quadratic Criteria v. 1

    • 1st Edition
    • Volume 40A
    • Bellman
    • English
    This work discusses the theory of control processes. The extremely rapid growth of the theory, associated intimately with the continuing trend toward automation, makes it imperative that the courses of this nature rest upon a broad basis. The work discusses the fundamentals of the calculus of variations, dynamic programming, discrete control processes, use of the digital computer, and functional analysis. Introductory courses in control theory are essential for training the modern graduate student in pure and applied mathematics, engineering, mathematical physics, economics, biology, operations research, and related fields. The work also describes the dual approaches of the calculus of variations and dynamic programming in the scalar case and illustrates ways to tackle the multidimensional optimization problems.
  • Graphs, Dynamic Programming and Finite Games

    • 1st Edition
    • Volume 36
    • Kaufmann
    • English
  • Differential Equations

    Stability, Oscillations, Time Lags
    • 1st Edition
    • Volume 23
    • Halanay
    • English
  • Advances in Computers

    • 1st Edition
    • Volume 6
    • English
    Volume 6 reflects the editors’ conviction that application of digital computers to areas akin to human thinking—machine-aid... cognition, to borrow a term from another environment—is one of the most active frontiers of development in our time. Articles in this volume deal with two such areas: information retrieval and what is called “ultraintelligent machines.”
  • Advances in Computers

    • 1st Edition
    • Volume 7
    • English