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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.

  • Practical Neural Network Recipies in C++

    • 1st Edition
    • Masters
    • English
    This text serves as a cookbook for neural network solutions to practical problems using C++. It will enable those with moderate programming experience to select a neural network model appropriate to solving a particular problem, and to produce a working program implementing that network. The book provides guidance along the entire problem-solving path, including designing the training set, preprocessing variables, training and validating the network, and evaluating its performance. Though the book is not intended as a general course in neural networks, no background in neural works is assumed and all models are presented from the ground up.The principle focus of the book is the three layer feedforward network, for more than a decade as the workhorse of professional arsenals. Other network models with strong performance records are also included.Bound in the book is an IBM diskette that includes the source code for all programs in the book. Much of this code can be easily adapted to C compilers. In addition, the operation of all programs is thoroughly discussed both in the text and in the comments within the code to facilitate translation to other languages.
  • Readings in Groupware and Computer-Supported Cooperative Work

    Assisting Human-Human Collaboration
    • 1st Edition
    • Ronald M. Baecker
    • English
    This comprehensive introduction to the field represents the best of the published literature on groupware and computer-supported cooperative work (CSCW). The papers were chosen for their breadth of coverage of the field, their clarity of expression and presentation, their excellence in terms of technical innovation or behavioral insight, their historical significance, and their utility as sources for further reading. Taken as a whole, the papers and their introductions are a complete sourcebook to the field. This book will be useful for computer professionals involved in the development or purchase of groupware technology as well as for researchers and managers. It should also serve as a valuable text for university courses on CSCW, groupware, and human-computer interaction.
  • Morphogenesis

    • 1st Edition
    • Volume 3
    • P.T. Saunders
    • English
    The collected works of Turing, including a substantial amount of unpublished material, will comprise four volumes: Mechanical Intelligence, Pure Mathematics, Morphogenesis and Mathematical Logic. Alan Mathison Turing (1912-1954) was a brilliant man who made major contributions in several areas of science. Today his name is mentioned frequently in philosophical discussions about the nature of Artificial Intelligence. Actually, he was a pioneer researcher in computer architecture and software engineering; his work in pure mathematics and mathematical logic extended considerably further and his last work, on morphogenesis in plants, is also acknowledged as being of the greatest originality and of permanent importance. He was one of the leading figures in Twentieth-century science, a fact which would have been known to the general public sooner but for the British Official Secrets Act, which prevented discussion of his wartime work. What is maybe surprising about these papers is that although they were written decades ago, they address major issues which concern researchers today.
  • Artificial Intelligence, Expert Systems & Symbolic Computing

    • 1st Edition
    • E.N. Houstis + 1 more
    • English
    This volume contains papers in the areas of artificial intelligence, expert systems, symbolic computing and applications to scientific computing. Together, they provide an excellent overview of the dynamic state of these closely related fields. They reveal a future where scientific computation will increasingly involve symbolic and artificial intelligence tools as these software systems become more sophisticated; also a future where systems of computational science and engineering will be problem solving environments created with components from numerical analysis, computational geometry, symbolic computing and artificial intelligence.