Information systems course
This page collects some information about courses at Caltech in the area of "information systems" (roughly, communications, computing, control and networking). This page was prepared in preparation for a faculty discussion on the a new information systems course that would be taught jointly by faculty in CDS, CS and EE.
Background and Goals
This course covers the fundamental mathematics of information systems, including key concepts and theories from communications, computer science, control theory, information theory and networking. Topics include: mathematical representations of information, signals and systems, computational complexity, fundamental limits of feedforward and feedback systems (Bode/Shannon), applications of graph theory to distributed systems.
Overview of current courses
CDS 110ab (Introduction to Control Systems)
Catalog listing An introduction to analysis and design of feedback control systems, including classical control theory in the time and frequency domain. Modeling of physical, biological, and information systems using linear and nonlinear differential equations. Stability and performance of interconnected systems, including use of block diagrams, Bode plots, the Nyquist criterion, and Lyapunov functions. Robustness and uncertainty management in feedback systems through stochastic and deterministic methods. Introductory random processes, Kalman filtering, and norms of signals and systems. The first term of this course is taught concurrently with CDS 101, but includes additional lectures, reading, and homework that is focused on analytical techniques for design and synthesis of control systems. Dependent courses (CDS 110a):
Partially overlapping courses

Topics (200809)

CDS 212/213
Catalog listing (a) Introduction to modern control systems with emphasis on the role of control in overall system analysis and design. Examples drawn from throughout engineering and science. Open versus closed loop control. Statespace methods, time and frequency domain, stability and stabilization, realization theory. Timevarying and nonlinear models. Uncertainty and robustness. (b) Linear systems, realization theory, time and frequency response, norms and performance, stochastic noise models, robust stability and performance, linear fractional transformations, structured uncertainty, optimal control, model reduction, m analysis and synthesis, real parametric uncertainty, Kharitonov’s theorem, uncertainty modeling. Dependent courses
Partially overlapping courses

Topics (200708)

CS/EE 145
Catalog listing This course introduces the basic mechanisms and protocols in communication networks, and mathematical models for their analysis. Part a covers topics such as digitization, switching, switch design, routing, error control (ARQ), flow control, layering, queuing models, optimization models, basics of protocols in the Internet, wireless networks, and optical networks. Part b covers current research topics in the design, analysis, control, and optimization of networks, protocols, and applications. In part c, students are expected to execute a substantial project in networking, write up a report describing their work, and make a presentation. CS 145 b may be repeated for credit with the instructor’s permission. Dependent courses
Partially overlapping courses 
Topics (200708)

EE 163
Catalog listing Least mean square error linear filtering and prediction. Mathematical models of communication processes; signals and noise as random processes; sampling and quantization; modulation and spectral occupancy; intersymbol interference and synchronization considerations; signaltonoise ratio and error probability; optimum demodulation and detection in digital baseband and carrier communication systems. Dependent courses
Partially overlapping courses

Topics (200708)

Course listings
The course listings below are from the Caltech catalog, mainly to serve as a reference for the rest of the information on this page.
CDS 110 ab. Introductory Control Theory. 12 units (309) first, 9 units (306) second terms. Prerequisites: Ma 1 and Ma 2 or equivalents; ACM 95/100 may be taken concurrently. An introduction to analysis and design of feedback control systems, including classical control theory in the time and frequency domain. Modeling of physical, biological, and information systems using linear and nonlinear differential equations. Stability and performance of interconnected systems, including use of block diagrams, Bode plots, the Nyquist criterion, and Lyapunov functions. Robustness and uncertainty management in feedback systems through stochastic and deterministic methods. Introductory random processes, Kalman filtering, and norms of signals and systems. The first term of this course is taught concurrently with CDS 101, but includes additional lectures, reading, and homework that is focused on analytical techniques for design and synthesis of control systems.
CDS 212. Introduction to Modern Control. 9 units (306); first term. Prerequisites: ACM 95/100 abc or equivalent; CDS 110 ab or equivalent. Introduction to modern control systems with emphasis on the role of control in overall system analysis and design. Examples drawn from throughout engineering and science. Open versus closed loop control. Statespace methods, time and frequency domain, stability and stabilization, realization theory. Timevarying and nonlinear models. Uncertainty and robustness.
CDS 213. Robust Control. 9 units (306); second term. Prerequisites: CDS 212, CDS 201. Linear systems, realization theory, time and frequency response, norms and performance, stochastic noise models, robust stability and performance, linear fractional transformations, structured uncertainty, optimal control, model reduction, m analysis and synthesis, real parametric uncertainty, Kharitonov’s theorem, uncertainty modeling.
CS/EE 145 abc. Networking. 9 units (333) first, second terms; (009) third term. Prerequisite: Ma 2 ab; instructor’s permission required for part c. This course introduces the basic mechanisms and protocols in communication networks, and mathematical models for their analysis. Part a covers topics such as digitization, switching, switch design, routing, error control (ARQ), flow control, layering, queuing models, optimization models, basics of protocols in the Internet, wireless networks, and optical networks. Part b covers current research topics in the design, analysis, control, and optimization of networks, protocols, and applications. In part c, students are expected to execute a substantial project in networking, write up a report describing their work, and make a presentation. CS 145 b may be repeated for credit with the instructor’s permission.
EE 111. Signals, Systems, and Transforms. 9 units (306); first term. Prerequisites: Ma 1, Ma 2. EE 45 recommended. An introduction to continuous and discrete time signals and systems. Study of the Fourier transform, Fourier series, the Laplace transform, Ztransforms, and the fast Fourier transform as applied in electrical engineering. Various types of systems, with emphasis on linear and time invariant systems. Transfer functions, difference and differential equations, state space representations, system realizations with block diagrams, and analysis of transient and steady state responses. Sampling theorems for analog to digital conversion.
EE 113. Feedback and Control Circuits. 12 units (444); third term. Prerequisite: EE 45 or equivalent. This class studies the design and implementation of feedback and control circuits. The course begins with an introduction to basic feedback circuits, using both op amps and transistors. These circuits are used to study feedback principles, including circuit topologies, stability, and compensation. Following this, basic control techniques and circuits are studied, including PID (ProportionalIntegratedDerivative) control, digital control, and fuzzy control. There is a significant laboratory component to this course, in which the student will be expected to build, analyze, test, and measure the circuits and systems discussed in the lectures.
EE/Ma 126 ab. Information Theory. 9 units (306); first, second terms. Prerequisite: Ma 2. Shannon’s mathematical theory of communication, 1948–present. Entropy, relative entropy, and mutual information for discrete and continuous random variables. Shannon’s source and channel coding theorems. Mathematical models for information sources and communication channels, including memoryless, first order Markov, ergodic, and Gaussian. Calculation of capacitycost and ratedistortion functions. Kolmogorov complexity and universal source codes. Side information in source coding and communications. Network information theory, including multiuser data compression, multiple access channels, broadcast channels, and multiterminal networks. Discussion of philosophical and practical implications of the theory. This course, when combined with EE 112, EE/Ma 127 ab, EE 161, and/or EE 167 should prepare the student for research in information theory, coding theory, wireless communications, and/or data compression.
EE 128 ab. Signal Processing Structures, Multirate Systems, and Statistical Signal Processing. 9 units (306); first, second terms. Prerequisite: EE 111 or equivalent required, and EE 112 or equivalent recommended. Multirate signal processing topics include decimation, interpolation, filter banks, polyphase filtering, advanced filtering structures, nonuniform sampling, data compression, and wavelets; and statistical signal processing topics include linear prediction, antenna array processing, radar signal processing, and optimal transceivers for digital communication systems.
EE 160. CommunicationSystem Fundamentals. 9 units (306); second term. Prerequisite: EE 111. Laws of radio and guided transmission, noise as a limiting factor, AM and FM signals and signaltonoise ratio, sampling and digital transmission, errors, information theory, error correction. Emphasis will be on fundamental laws and equations and their use in communicationsystem designs, including voice, video, and data.
EE 161. Wireless Communications. 9 units (306); third term. Prerequisite: EE 160. This course will cover the fundamentals of wireless channels and channel models, wireless communication techniques, and wireless networks. Topics include statistical models for timevarying narrowband and wideband channels, fading models for indoor and outdoor systems, macro and microcellular system design, channel access and spectrum sharing using TDMA, FDMA, and CDMA, timevarying channel capacity and spectral efficiency, modulation and coding for wireless channels, antenna arrays, diversity combining and multiuser detection, dynamic channel allocation, and wireless network architectures and protocols.
EE 163 ab. Communication Theory. 9 units (306); second, third terms. Prerequisite: EE 111; ACM/EE 116 or equivalent. Least mean square error linear filtering and prediction. Mathematical models of communication processes; signals and noise as random processes; sampling and quantization; modulation and spectral occupancy; intersymbol interference and synchronization considerations; signaltonoise ratio and error probability; optimum demodulation and detection in digital baseband and carrier communication systems.
EE 164. Stochastic and Adaptive Signal Processing. 9 units (306); third term. Prerequisite: ACM/EE 116 or equivalent. Fundamentals of linear estimation theory are studied, with applications to stochastic and adaptive signal processing. Topics include deterministic and stochastic leastsquares estimation, the innovations process, Wiener filtering and spectral factorization, statespace structure and Kalman filters, array and fast array algorithms, displacement structure and fast algorithms, robust estimation theory and LMS and RLS adaptive fields.