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  • CS 123: Projects in Database Systems

    9.00 Credits
    California Institute of Technology

    Students are expected to execute a substantial project in databases, write up a report describing their work, and make a presentation. Instructor: Pinkston. Prerequisite:    CS121 and CS122.
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  • CS 127: Error-Correcting Codes

    9.00 Credits
    California Institute of Technology

    This course develops from first principles the theory and practical implementation of the most important techniques for combating errors in digital transmission or storage systems. Topics include algebraic block codes, e.g., Hamming, BCH, Reed-Solomon (including a self-contained introduction to the theory of finite fields); and the modern theory of sparse graph codes with iterative decoding, e.g. LDPC codes, turbo codes, fountain coding. Emphasis will be placed on the associated encoding and decoding algorithms, and students will be asked to demonstrate their understanding with a software project. Instructor: Ho.
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  • CS 129 abc: Information and Complexity

    9.00 Credits
    California Institute of Technology

    A basic course in information theory and computational complexity with emphasis on fundamental concepts and tools that equip the student for research and provide a foundation for pattern recognition and learning theory. what information is and what computation is; entropy, source coding, Turing machines, uncomputability. topics in information and complexity; Kolmogorov complexity, channel coding, circuit complexity, NP-completeness. theoretical and experimental projects on current research topics. Not offered 2012–13.
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  • CS 132 ab: Advanced Robotics: Navigation and Vision

    9.00 Credits
    California Institute of Technology

    The course focuses on current topics in robotics research in the area of autonomous navigation and vision. Topics will include mobile robots, multilegged walking machines, use of vision in navigation systems. The lectures will be divided between a review of the appropriate analytical techniques and a survey of the current research literature. Course work will focus on an independent research project chosen by the student. Instructor: Matthies.
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  • CS 133: Electricity Markets

    9.00 Credits
    California Institute of Technology

    This in depth introductory course provides an overview of the industry focusing on the linkages between power system engineering, markets, and regulatory policy. We will analyze the fundamentals of various electricity markets including locational marginal pricing, bilateral, day-ahead, real-time, capacity, emissions markets and risk markets. We will identify the basic components, design, and operation of electric power systems. We will examine how markets should be designed to be consistent with the engineering fundamentals of electric power systems. We will discuss sensors, metering devices, communication, and computation required to enable markets to functions. Not offered 2012–13.
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  • CS 135: Power System Analysis

    9.00 Credits
    California Institute of Technology

    Phasor representation, 3-phase transmission system, per-phase analysis; power system modeling, transmission line, transformer, generator; network matrix, power flow solution, optimal power flow; Swing equation, stability, protection; demand response, power markets. Instructor: Low.
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  • CS 138 abc: Computer Algorithms

    9.00 Credits
    California Institute of Technology

    Design and analysis of algorithms. Techniques for problems concerning graphs, flows, number theory, string matching, data compression, geometry, linear algebra and coding theory. Optimization, including linear programming. Randomization. Basic complexity theory and cryptography. Not offered 2012–13. Prerequisite:    CS 21 and CS 38, or instructor’s permission.
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  • CS 139 abc: Concurrency in Computation

    9.00 Credits
    California Institute of Technology

    Design and verification of concurrent algorithms. Topics: different models of concurrent computations; process synchronization by shared variables and synchronization primitives; distributed processes communicating by message exchange; the concepts of synchronization, indivisible actions, deadlock, and fairness; semantics and correctness proofs; implementation issues; and application to VLSI algorithm design. Parallel machine architecture issues include mapping a parallel algorithm on a network of processors, and classical parallel algorithms and their complexity. Not offered 2012–13. Prerequisite:    CS 21 and CS 38, or instructor’s permission.
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  • CS 141 abc: Distributed Computation Laboratory

    9.00 Credits
    California Institute of Technology

    This laboratory course deals with the systematic design and implementation of high-confidence scalable networks of communicating objects that discover other objects, configure themselves into collaborating groups of objects, and adapt to their environment. Teams of students explore theories and methods of implementation to obtain predictability and adaptability in distributed systems. Each team of students is expected to submit a research paper at the end of the third term, schedule demonstrations periodically, and maintain documents describing their project status. Instructor: Chandy; Part c not offered 2012-13. Prerequisite:    CS 3, CS 21 and CS 38, or instructor’s permission.
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  • CS 143: Communication Networks

    9.00 Credits
    California Institute of Technology

    This course introduces the basic mechanisms and protocols in communication networks, and mathematical models for their analysis. It covers topics such as digitization, switching, switch design, routing, error control (ARQ), congestion control, layering, queuing models, optimization models, basics of protocols in the Internet, wireless networks, and optical networks. Instructor: Low. Prerequisite:    Ma 2 ab, CS 24 and CS 38, or instructor permission.
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