Information Technology Courses (INFT)

Graduate courses listed under the Departments of Computer Science, Electrical and Computer Engineering, Information and Software Systems Engineering, Systems Engineering, Operations Research and Engineering, and Applied and Engineering Statistics are appropriately considered as courses forming an inherent part of this program.

Related Catalog Entry: School of Information Technology and Engineering

Related Mason Website: School of Information Technology and Engineering (http://ite.gmu.edu/)

100 Information Technology in Action (1:1:0).Prerequisite: Permission of instructor. Designed for students pursuing the IT minor. Introduction to current issues as well as career-related opportunities in the IT field. Appreciation of the manifold implications of technological change, and motivation for continued, enthusiastic learning in the area of IT.

500 Quantitative Foundations for Information Systems Analysis (3:3:0). Prerequisite: MATH 108 or an equivalent one-semester undergraduate introductory calculus course covering both differential and integral calculus. A course providing a common background in basic quantitative areas focused on decision making and information processing. Topics include a review of basic calculus, matrix algebra, problems in optimization, and the calculus of probabilities.

746/CSI 776 Calculus of Random Signals (3:3:0).Prerequisite: STAT 652 or ECE 630 or 632. An introduction to modern theory of stochastic calculus such as stochastic integrals, martingales, counting processes, diffusion processes, and Ito-type processes in general. The course presents applications of the methods to engineering and biology. The focus is on developing the necessary concepts rather than mathematical proofs. This course is suited for graduate students in information technology, electrical engineering, mathematics, operations research, and statistics.

776/CSI 778 Real Analysis and Statistics (3:3:0).Prerequisites: STAT 652 or ECE 620, 621, and 630. Advanced calculus and linear algebra needed for doctoral work in statistics and related fields. Topology, vector spaces, matrices, continuity, differentiation, sequences and series of real numbers and real-valued functions, Riemann and Riemann-Stieltjes integrals, and multidimensional calculus. Applications in probability and statistics including response surface methodology are presented.

796, 797 Directed Reading and Research (1-3:0:0). Reading and research on a specific topic in information technology under the direction of a faculty member. May be repeated as needed.

800, 801 Doctoral Seminar in Information Technology (1:1:0). A weekly seminar in information technology with interactive participation by students, faculty, and invited specialists. May be repeated as needed.

803, 804 Doctoral Tutorial in Information Technology (3:3:0). Individualized intensive study of particular aspects of information technology. May be repeated as needed.

811 Principles of Machine Learning and Inference (3:3:0).Prerequisite: CS 580, CS 681, or permission of instructor. A presentation of unifying principles that underlie diverse methods, paradigms, and approaches to machine learning and inference. The course also reviews the most known learning and inference systems, discusses their strengths and limitations, and suggests the most appropriate areas of their application. Students get a hands-on experience by experimenting with the state-of-the-art learning and inference systems and work on projects tailored to their research interests.

812 Advanced Topics in Natural Language Processing (3:3:0).Prerequisite: CS 680. Advanced treatment of topics in syntax, semantics, and generation of linguistic output. Implementation and applications are also discussed.

813 Seminar: Intelligent Tutoring Systems (3:3:0).Prerequisite: CS 689. Current research topics in intelligent tutoring systems and learning environments, including case studies in selected domains, such as medicine and foreign language. Relevant recent advances in closely related subfields of artificial intelligence are presented, as appropriate. Topics may include semantically constrained exploration, student modeling, example generation, formalization of pedagogical decision-making, and evaluation strategies. May be repeated for credit with a change in topic.

814/CSI 801 Foundations of Computational Science (3:3:0).Prerequisite: CS 735 or equivalent. Investigation methods for scientific questions in the presence of teraops computation, gigabyte memory, and gigabit transmission. Mapping of mathematical models to parallel algorithm and architectures, associated data structures, languages, operating systems, networks, and global change demonstrate important scientific accomplishments enabled by computation. Working in teams with scientists and information technologists, students learn the mathematical models, abstract algorithms, and concrete algorithms for these cases, and conduct experiments and simulations with them.

815 Parallel Computation (3:3:0).Prerequisite: CS 635 or INFT 816 or CSI 801. Topics illustrating some of the contemporary thinking on architectures, application, development environments, algorithms, operating system related issues, language requirements, and performance for parallel computation.

816 Parallel Architectures, Algorithms, and Applications (3:3:0).Prerequisites: CS 583 and computer architecture course. Familiarization for students in area of parallel architectures, algorithms, and parallel computers. Various algorithms and their applicability to certain architectures are discussed. Comparisons of these parallel algorithms with certain tools are studied, and applications to artificial intelligence, image processing, and database machines are explored.

817 Neural Networks (3:3:0).Prerequisite: CS 688 or permission of instructor. A study of adaptive and competitive principles using distributed and parallel computation. Topics include background from statistics, control, adaptive signal processing, and neurosciences. Basic models, such as those suggested by Grossberg, Hopfield, and Kohonen, are discussed in terms of their analytical characteristics and applications. Neural networks are assessed as universal approximators. Connections to the fuzzy approach are established through the Radial Basis Function approach. Applications to perception, knowledge-based systems, and robotics are presented.

818 Topics in High Performance Computer Systems (3:3:0).Prerequisites: CS 571 and CS 635, or permission of instructor. Discussion of current research topics in high-performance computer systems. Topics vary according to student and faculty interest. Possible topics include mass storage systems for supercomputers, distributed file systems, operating systems and system software for massively parallel computers, and heterogeneous distributed computing.

819 Computational Models for Probabilistic Inference (3:3:0).Prerequisite: SYST 664 or 652. Graphical models for encoding conditional independence assumptions in a multivariate discrete probability distribution. The course includes computational methods for updating probabilities when evidence is observed on some variables in the model. Algorithms for finding the most probable instantiation of the network. Applications in expert systems and decision analysis.

821 Software Engineering Seminar (3:3:0).Prerequisite: SWSE 621. A study of the application of software engineering principles, design methods, and support tools through real-life problems extracted from faculty/industry projects. May be repeated with a change in topic.

822 Software Maintenance and Reuse (3:3:0).Prerequisites: CS/SWSE 621 (or equivalent), data structures, principles of modern programming, discrete mathematics; or permission of instructor. Perfective maintenance, reuse of software components and patterns, evolving software systems, principles of object-oriented analysis and development. Issues regarding technologies supporting perfective software maintenance and reuse are presented.

823 Software for Critical Systems (3:3:0).Prerequisites: SWSE 620 and STAT 554. A study of software for systems in which failure can be catastrophic. Techniques to construct and analyze software for critical applications and examination of inherent limitations of such techniques are presented, as well as interaction between techniques used during development and behavior of software during operation. Topics include tolerance of software faults, design redundancy, data redundancy, software safety, formal methods, statistical testing, design for analyzability, and design for testability.

830 Detection and Estimation Theory (3:3:0).Prerequisites: ECE 528 and 734, or permission of instructor. An introduction to detection and estimation theory with communication applications. Topics include M-hypotheses, Bayes, minimax, Neyman-Pearson criterion, detection of signals in AWGN and ACGN, Bayes estimation, ML estimation of signal parameters in AWGN and ACGN, estimation of Gaussian waveforms in Gaussian noise, linear MSE estimation, and Kalman and Wiener filters.

832 Speech and Image Coding (3:3:0).Prerequisites: ECE 535 and 632. A study of waveform coding concepts and algorithms and their applications to the analysis and design of data compression systems. Specific schemes involving speech and image coding are discussed. Topics include statistical properties of speech and image signals, rate distortion theory, predictive and adaptive coding techniques, optimum quantization, and bit assignment algorithms.

833 Satellite Communication (3:3:0).Prerequisite: ECE 631. An introduction to the theory and applications of modern satellite communications. Topics include satellite channel characterization, channel impairment and transmission degradation, link calculations, modulation, coding, multiple access, broadcasting, random access schemes, demand assignment, synchronization, satellite switching and onboard processing, integrated service digital satellite networks, and satellite transponder, ground stations, packet switching, and optical satellite communications.

834 Telecommunications Networks (3:3:0).Prerequisites: ECE 528 and 642, or permission of instructor. Open Systems Interconnection Reference Model, analysis and modeling of layered network architectures including transport and higher layers, performance evaluation of System Network Architecture, DEC Network Architecture, and other telecommunication architectures; protocols and standards for local, metropolitan, and wide area networks. Topics include high-speed packet switching, broadband multimedia protocols, and congestion control in broadband integrated networks.

835 Computational Vision (3:3:0).Prerequisites: CS 682 and 686, or permission of instructor. A study of recent advances in development of machine vision algorithms and knowledge-based vision systems. Topics include scalespace; Gabor and wavelet processing; distributed and hierarchical processing using neural networks; motion analysis; active, functional, and selective perception; object and target recognition; expert systems; data fusion; and machine learning. Emphasis is on system integration in terms of perception, control, action, and adaptation. Applications to robotics, intelligent highways, inspection, forensic, and data compression are presented.

836 Special Topics in Detection and Estimation Theory (3:3:0).Prerequisite: ECE 734. Advanced topics in detection, estimation, and signal processing in areas of current research interest. Topics may include spectral estimation, speech recognition, array processing, SAR, underwater acoustics, or higher order spectra.

837 Optimum Array Processing I (3:3:0).Prerequisite: ECE 528 and 734. Optimum antenna array processing for communications, radar, and sonar systems. Classical synthesis of linear and planar arrays. Characterization of space-time processes. Spatial AR and ARMA models. Optimum waveform estimation. MVDR and MMSE estimators. LCMV beamformers. Generalized sidelobe cancelers. Robust algorithms. Diagonal loading.

838 Signal Processing Algorithms and Architectures (3:3:0).Prerequisite: ECE 635 or permission of instructor. A study of recent advances in the development of fast-signal processing algorithms and parallel architectures. Topics include fast transforms, multirate processing of digital signals, adaptive filtering, high-resolution spectral analysis, parallel computational arrays, and mapping of signal processing algorithms into array processors.

840 Advanced Robotics (3:3:0).Prerequisite: ECE 650 or CS 580, or permission of instructor. A review of state-of-the-art in theoretical and software aspects of robotics. Topics include compliance, flexible manipulators, intelligent task planning, collision avoidance, grasping and pushing, dexterous manipulation with multifingered hands, coordination of multiple manipulators, legged locomotion, autonomous navigation, robot languages, intelligent control, integration of sensory information, visual serving, and robot learning.

841 Kalman Filtering with Applications (3:3:0).Prerequisite: ECE 521 and 528, or equivalent, or permission of instructor. A detailed treatment of Kalman Filtering Theory and its applications, including some aspects of stochastic control theory. Topics include state-space models with random inputs, optimum state estimation, filtering, prediction and smoothing of random signals with noisy measurements, all within the framework of Kalman filtering. Additional topics are nonlinear filtering problems, computational methods, and various applications such as Global Positioning System, tracking, system control and others. Stochastic control problems include linear-quadratic-Gaussian problem and minimum-variance control.

842 Models of Probabilistic Reasoning (3:3:0).Prerequisite: STAT 544 and OR 681. A survey of alternative views about how incomplete, inconclusive, and possibly unreliable evidence might be evaluated and combined. Among the views discussed are the Bayesian, Baconian, Shafer-Dempster, and Fuzzy systems for probabilistic reasoning.

843 Computer-Aided Control System Design (3:3:0).Prerequisite: ECE 620 or 624. An investigation of available computer-aided design (CAD) methods and current research in application of artificial intelligence to the CAD of dynamic systems. Applications in computer-aided control system design are presented. Topics include control system design using existing CAD methods, representation of design knowledge, integration of algorithmic and heuristic approaches to system design, intelligent user interfaces for CAD, and intelligent design tutors.

844 Pattern Recognition (3:3:0).Prerequisite: ECE 528, CS 580, CS 688, or equivalents. A study of the fundamentals of statistical pattern recognition, functional and density approximation, and adaptive systems. Topics include the Bayesian approach, non-parametric statistics and neural networks, adaptive fuzzy systems and control, Bayesian nets and Hidden Markov Models (HMM), and evolutionary computation and genetic algorithms. Applications to clustering and recognition, time-series prediction and model-based identification, forensics, and knowledge-mining are presented.

845 High-Frequency Electronics (3:3:0).Prerequisite: ECE 520. A study of devices and circuits used in high-speed communication systems. Topics include microwave bipolar transistors, GaAs MOSFETs, and high-speed integrated circuits; and the design of linear and power amplifiers using S-parameter techniques and computer simulation.

846 Optical Signal Processing (3:3:0).Prerequisite: ECE 565. A study of optical systems for processing temporal signals and images. Topics include use of coherent optical systems for image processing and pattern recognition, principles of holography, acousto-optic systems for radar signal processing, and optical computers.

847 Topics in Photonics (3:3:0).Prerequisite: ECE 565 or permission of instructor. An in-depth discussion of specific topics in photonics. Topics include optical storage (disks, holographic, 3D), digital optical computing, integrated optics, photonic switching networks, and optoelectronic devices. May be repeated when covering different topics.

848 Digital Video Communications (3:3:0).Prerequisites: ECE 535 and 642. Coding, transport, and modeling of digital video signals; digital coding of waveforms with emphasis on compression techniques for video signals, transform coding including DCT and rate distortion theory for images, subband/wavelet coding of images, treatment of video signals for different television formats, colorimetry and motion estimation/compensation, general characterization of video traffic, modeling of variable bit rate video codecs, transport protocols for video and multimedia, network-delay compensation for video over ATM, VBR video flow control, discussion of applications ranging from HDTV/TV over ATM, digital HDTV for terrestrial broadcast, to videoconferencing/desktop multimedia over LAN/WAN.

850 Seminar: Topics in Systems Integration Engineering (3:3:0).Prerequisite: SYST 720 or equivalent. An analysis of the Systems Integration life cycle and the tools, techniques, and methods that contribute to the design, development, application, and evaluation of approaches to systems integration. The course reviews the current technological advances that support systems integration methods, including functional and nonfunctional SI requirements, risk assessment and risk management, internal protest avoidance mechanisms, and protest management. May be repeated when the topic is different.

851 Seminar: Topics in Software Requirements (3:3:0).Prerequisite: SWSE 620 or SWSE 624 or CS 624. An emphasis on the latest research ideas in the requirements engineering domain. The course discusses the current state-of-the-art and state-of-the-practice in requirements engineering. It focuses on the most critical problems and discusses how their resolutions might further the requirements research knowledge base and enhance the quality and productivity of real software and system developments in industry. May be repeated when the topic is different.

852 Graphical Real-Time Simulation (3:3:0).Prerequisite: CS 652 or INFT 875. Current research in advanced computer graphics and its applications in realistic real-time simulations. Topics include physically based modeling, real-time simulation, distributed interactive simulation (DIS), network virtual environments (NVE), and virtual reality (VR).

857 Automated Planning and Problem Solving (3:3:0).Prerequisite: CS 580. An introduction to automated planning and problem solving in artificial intelligence. Students learn a broad set of techniques in automated planning and heuristic searching along with strategies for implementing automated problem-solving systems using these methods. Topics include heuristic search, predicate calculus, nonmonotonic logic, action planning, adversarial planning, multiagent planning, and logic models for reasoning about action and time.

858 Logic Models in Artificial Intelligence (3:3:0).Prerequisite: CS 580. An examination of the relevance of logic theory to artificial intelligence. The course familiarizes students with a variety of formal logics that are used in artificial intelligence, as well as ongoing research in new logics. Topics include first-order predicate calculus, resolution and nonresolution theorem proving, nonmonotonic logic, assumption-based reasoning, the relationship between symbolic and quantitative theories of uncertainty, temporal logics, and their application to planning and metareasoning.

860 Software Analysis and Design of Real-Time Systems (3:3:0).Prerequisite: SWSE 623. A background for students who want to conduct research in the software engineering of real-time systems. Students gain an understanding of key real-time software system analysis, design concepts and methods, and how they are used in the development of large-scale, real-time software systems. Students also gain an understanding of the potential impact of emerging technologies in this field. A term project in the design and analysis of a complex real-time software system is undertaken.

861 Distributed Database Management Systems (3:3:0).Prerequisite: INFS 614 or equivalent. Topics in distributed database management including transaction management, concurrency control, deadlocks, replicated database management, query processing reliability, and surveys of commercial systems and research prototypes.

862 Formal Models for Computer Security (3:3:0).Prerequisite: INFS 762. A study of formal mathematical models for computer security. Mathematical properties of these models are identified and analyzed. The models are compared with respect to formal and pragmatic criteria. The models include lattice-based models, noninterference models, models based on propagation of access rights, multilevel data models, integrity models, and miscellaneous models such as the n-tree model for group authorization.

863 Empirical Methods in Information Technology (3:3:0).Prerequisite: STAT 654. An examination of alternative paradigms of scientific research and their applicability to research in information technology. Topics include fundamental elements of scientific investigation, basic principles of experimental design and statistical induction, philosophy of science and its relation to the information technology sciences, and case studies of information technology research.

864 Scientific Databases (3:3:0).Prerequisite: INFS 614. A study of database support for scientific data management. Requirements and properties of scientific databases, data models for statistical and scientific databases; semantic and object-oriented modeling of application domains; statistical database query languages and query optimization; advanced logic query languages; and case studies such as the human genome project and the earth orbiting satellite are covered.

865 Networks and Distributed Systems Security (3:3:0).Prerequisite: INFS 762 or permission of instructor. A detailed study of network and distributed systems security. The course reviews basic cryptography, and threats and vulnerabilities in distributed systems. Security services--confidentiality, authentication, integrity, access control, nonrepudiation, and their integration in network protocols--are covered. Topics also include key management, cryptographic protocols and their analysis; access control, delegation, and revocation in distributed systems; and security architectures, multilevel systems, and security management and monitoring.

867 Intelligent Databases (3:3:0).Prerequisite: INFS 760 or permission of instructor. A study of models and techniques that empower database systems with intelligent and cooperative behavior, with emphasis on subjects: knowledge-rich databases, logic databases, epistemological queries, intentional answering, and knowledge discovery. Topics include user interfaces--cooperative query interfaces, interactive query constructors, graphical interfaces, and browsers; and uncertainty--representing, manipulating, and retrieving uncertain, imprecise, or incomplete information, and formulating and interpreting vague or incomplete queries.

874 Analysis of Complex Surveys (3:3:0).Prerequisites: STAT 656, 665, and 674 or permission of instructor. A presentation of current theory and methods of statistical analysis of data from complex surveys of finite populations. The course includes contingency table analysis and regression analysis; modeling structured populations by multilevel models; and loglinear, logistic, and regression models for stratified and multistage cluster samples. Case studies are used to illustrate the methodology.

875/CSI 803 Scientific and Statistical Visualization (3:3:0).Prerequisite: STAT 554 or CS 651. Presentation of visualization methods used to provide new insights and intuition concerning measurements of natural phenomena and scientific and mathematical models. Case study examples from a variety of disciplines to illustrate what can be done are presented. Topics include human perception and cognition, an introduction to the graphics laboratory, elements of graphing data, representation of space-time and vector variables, representation of 3D and higher dimensional data, dynamic graphical methods, and virtual reality. Students are required to work on a visualization project. The course emphasizes software tools on the Silicon Graphics workstation, but other workstations and software may be used for the project.

876/CSI 876 Measure and Linear Spaces (3:3:0).Prerequisite: INFT 776/CSI 778. Measure theory and integration, convergence theorems, and the theory of linear spaces and functional analysis, including normed linear spaces, inner product spaces, Banach and Hilbert spaces, Sobelev spaces, and reproducing kernels. Topics include wavelets, applications to stochastic processes, and nonparametric functional inference.

877/CSI 877 Geometric Methods in Statistics (3:3:0).Prerequisite: STAT 751 or permission of instructor. Modern multivariate statistical methods including visualization of multivariable data rely on geometric insight and methods. The course develops the foundations of geometric methods for statistics. Topics include n-dimension Euclidian geometry, projective geometry, differential geometry including curves, surfaces, and n-dimensional differentiable manifolds, and computational geometry including computation of convex hulls, and tessellations of 2-, 3-, and n-dimensional spaces. Examples include applications to statistics and scientific visualization.

879 Topics in Stochastic System Simulation (3:3:0).Prerequisite: OR 635 or permission of instructor. Special topics and recent developments in the Monte Carlo simulation methodology for discrete-event stochastic systems. Contents vary and possible topics include statistical analysis of simulation output data, random number and random ariate generation, variance reduction techniques, sensitivity analysis and optimization of simulation models, distributed and parallel simulation, object-oriented simulation, and specialized applications. May be repeated for credit when topics are distinctly different.

880 Queueing Modeling of Computer-Communication Networks (3:3:0).Prerequisite: OR 645, OR 647, ECE 542, or equivalents. A study of analytical modeling of computer and communication networks and performance evaluations. Topics include Markovian systems, open networks, closed networks, approximations, decomposition, simulation, sensitivity analysis, and optimal operation of systems. Local area networks, manufacturing systems, and other applications are presented.

881 Numerical Methods for Mathematical Optimization (3:3:0).Prerequisites: OR 641 or 642 or 643 or 644. A study of computational issues related to the solution of linear, integer, networks, and nonlinear programming problems. Topics may include the use of list processing, heuristic techniques, parallel processing, efficient inversion techniques, and numerical analysis procedures. Also included may be complexity analysis and the structure of algorithms, recent results relating to the worst case and average case performance of algorithms, and a survey of leading software. Students use, alter, and develop software throughout the course. May be repeated for credit when topics are distinctly different.

882 Advanced Topics in Combinatorial Optimizations (3:3:0).Prerequisites: OR 641 and 642. A study of problems using the most recent developments. Topics include cutting plane procedures based on polyhedral combinatorics, column-generation procedures for large, complex problems, heuristic approaches (genetic algorithms, simulated annealing, tabu search), the study of special structures, reformulation techniques and bounding approaches. Topics stress the most recent developments in the field. May be repeated for credit when topics are distinctly different.

884 Advanced Topics in Nonlinear Programming (3:3:0).Prerequisite: OR 644. A study of theory and algorithms for solving nonlinear optimization problems. Contents vary, and possible topics include large-scale and parallel unconstrained optimization, theoretical issues in constrained optimization, duality theory, Lagrangian and methods, and sequential quadratic programming methods. May be repeated for credit when topics are distinctly different.

885 Spectral Estimation (3:3:0).Prerequisite: ECE 535 or STAT 652 or permission of instructor. An in-depth study of spectral analysis and its application to statistical signal processing. Topics include classical Fourier analysis of deterministic signals and Wiener theory of spectral analysis for random processes; spectral estimation using the Periodogram and the window approaches; maximum entropy spectral estimation and its relation to autoregression modeling; signal subspace approaches for frequency estimation; and the wavelet transform and its relation to the short-time Fourier transform.

886 Information Theory (3:3:0).Prerequisite: ECE 630 or STAT 644 or equivalent or permission of instructor. An in-depth study of information theory and its application to communication theory. Topics include measures of information such as entropy, mutual information, and relative entropy; the asymptotic equipartition property; noiseless source coding; Universal Source Coding and the Lemple-Ziv algorithm; channel capacity and the channel coding theorem; the Gaussian channel; and rate distortion theory and quantization.

888 Distributed Estimation and Multisensor Tracking and Fusion (3:3:0). Prerequisite: ECE 528 or SYST 611. Centralized and distributed estimation theory, hierarchical estimation, tracking and data association, multisensor multitarget tracking and fusion, distributed tracking in distributed sensor networks, track-to-track association and fusion, and Bayesian networks for fusion.

910 Advanced Topics in Artificial Intelligence (3:3:0).Prerequisite: A graduate course in artificial intelligence. Special topics in artificial intelligence not occurring in the regular computer science sequence. The seminar format requires substantial student participation. Subject matter may include continuation of existing 600- or 700-level courses in artificial intelligence and/or other topics. May be repeated for credit when subject matter differs.

915 Advanced Topics in Parallel Computation (3:3:0).Prerequisite: INFT 815. A discussion of current research topics in parallel computation. Topics vary according to student and faculty interest. Possible topics include formal models of concurrency, specification and design of parallel programming languages, logic programming in a parallel environment, and parallel distributed processing (neural networks).

921 Advanced Software Engineering Seminar (3:3:0).Prerequisite: INFT 821 or 851. Advanced software engineering topics currently in research laboratories, or which have received only empirical treatment. Topics may include special application areas (as opposed to nontraditional applications), such as artificial intelligence, as well as important industry-related software issues that have far-reaching consequences, like software configuration management.

922 Concurrent Object-Oriented Systems (3:3:0).Prerequisite: INFT 822. A comparative study of existing concurrent object-oriented approaches to problem analysis and software construction. The course introduces current research issues in concurrent object-oriented systems, concurrency models, and concurrent object-oriented programming languages and development tools.

925 Advanced Topics in C3I Systems Engineering (3:3:0).Prerequisite: SYST 680/ECE 670. Special topics in C3I. Content varies in different terms. Representative areas include quantitative evaluation of C3 systems, applications of artificial intelligence in C3 systems, and military communications systems.

930 Multichannel Statistical Signal Processing (3:3:0).Prerequisite: INFT 830. A study of topics in multichannel estimation and detection theory, with emphasis on the multivariate gaussian noise model. Topics include multivariate distribution theory, including the Wishart, matric-t, and multivariate-beta distributions, considering radar and sonar signal processing applications; and the general linear model and its application in adaptive and signal processing. Other topics include spectral analysis via principal components, tests for the dependence of several stochastic inputs, and analysis of covariance structures.

931 Secure Telecommunication Systems (3:3:0).Prerequisites: ECE 632 and 633. An introduction to secure data and voice communications. Topics include theoretic basis of cryptography, random cipher systems, practical security schemes, linear and nonlinear shift registers and encryption algorithms, block encipher and NBS data encryption standard, public key cryptography, RSA, knapsack algorithms, digital signatures and authentication, security of computer networks, cryptographic protocols, key management, speech security, and voice scrambling.

932 Spread Spectrum Communications (3:3:0).Prerequisite: ECE 631. Fundamentals of spread spectrum communications. Major topics include pseudonoise spread spectrum systems, acquisition, synchronization, time-hopping, frequency hopping, and multiple-access communication.

933 Modeling and Analysis of Integrated Services Digital Networks (3:3:0). Prerequisites: ECE 631 and 642. A study of integrated services digital networks. Topics include queueing, modeling, and analysis of digital circuit-switching systems; integrated data and voice multiple access schemes; ISDN layered architectures; ISDN protocols; and transmission technologies and system implementations.

934 Advanced Topics in Detection and Estimation Theory (3:3:0).Prerequisite: INFT 830. Advanced topics in detection and estimation theory of current research interest. Areas may include adaptive array processing, direction-finding techniques using eigenspace techniques (e.g., MUSIC, ESPRIT), spectral estimation, and underwater acoustics applications.

935 Knowledge-Based Systems for Text Translation (3:3:0).Prerequisite: INFT 835 or equivalent. Current topics for text processing, analysis, and translation. Topics include automatic text reading and reconstruction systems; computational linguistics; syntax analysis; semantic analysis and interpretation; discourse analysis and information structuring; text generation; text abstractions; strategies in machine translation and R & D; sublanguages for automatic translation, knowledge-based machine translation; basic theory and methodologies in EUROTRA and GMTP projects; machine translation as an expert task; human-machine interaction in translation; and reflections on knowledge needed to process formed languages.

936 Advanced Computer Architecture Seminar (3:3:0).Prerequisite: ECE 641 or equivalent. Current topics of advanced research in computer architecture. Topics include data flow architecture; high-level language architectures; multiprocessors: structure, algorithms, operating systems, RISC vs. CISC architecture, and distributed systems. The course discusses commercial advanced architecture systems.

937 Optimum Array Processing II (3:3:0).Prerequisite: INFT 837. Adaptive beamformers. SMI and RLS estimators. Spatial smoothing and FB averaging. QR decomposition. LMS algorithm. Optimum detection. Optimum parameter estimation. UML and CML estimation. Cramer-Rao bounds. IQML. Weighted subspace fitting. Subspace algorithms: MUSIC, ESPRIT. Root-versions. Beamspace algorithms. Sensitivity, robustness, and calibration.

940 Advanced Topics in Control and Robotics (3:3:0).Prerequisites: ECE 620, 621, 624, and 650. Advanced and newly developed topics in control and robotics. The content varies depending on current faculty interests and student demand. Topics such as knowledge-based control, intelligent control, hierarchical and distributed control, robust control, and reasoning under uncertainty are included.

941 System Identification and Adaptive Control (3:3:0).Prerequisite: ECE 621 or permission of instructor. An advanced treatment of identification and adaptive control. Topics include identification algorithms, their convergence and accuracy, and computational aspects; model reference and self-tuning adaptive control, transients, stability and robustness; and intelligent schemes to improve robustness. Students are also required to study the literature and to complete a computer project.

943 Models of Approximate Reasoning (3:3:0).Prerequisite: INFT 842. A survey of mathematical tools and algorithms for the modeling and use of uncertain knowledge in approximate reasoning. Topics include Bayesian theory, fuzzy logic, the Dempster-Shafer theory, evidential reasoning, probabilistic logic, multiattribute utility theory, confirmation theory, theory of endorsements, nonmonotonic reasoning, default reasoning, measures of information, knowledge fusion, propagation of beliefs in networks, and applications to knowledge support systems.

944 The Process of Discovery and Its Enhancement in Engineering Applications (3:3:0).Prerequisite: INFT 842 or permission of instructor. A study of ingredients of imaginative reasoning as it concerns the efficient discovery of new ideas and valid evidential test of them. Topics include different interpretations of Peirce's theory of abductive reasoning, other forms of reasoning, Hintikka's analysis of the process of inquiry, and current attempts to design systems that provide assistance in discovery-related or investigative activities.

945 Advanced Topics in Microelectronics (3:3:0).Prerequisite: INFT 845. Current topics of advanced research in microelectronics. Topics include very high speed integrated circuits, monolithic microwave integrated circuits, optoelectronic integrated circuits, novel device structures, and advances in semiconductor device technology. May be repeated with a change in topic.

950 Design and Management Aspects of Information Systems (3:3:0).Prerequisite: INFS 790 or equivalent. The impact of organizations and management of information systems (IS) and vice versa. Topics include problems of introducing IS; the effect on organizational economic and political framework; participative design and new techniques for specification, analysis, design, and implementation of IS; rapid prototyping and expert systems; possible conflicts; methods in life-cycle management; and economic analysis.

951 Software Productivity (3:3:0).Prerequisite: INFT 821 or 851. An analysis of technologies and methodologies of the systems approach to software engineering theory and application, decision support and knowledge-based systems for enhancing software productivity. The course covers macroenhancement approaches to increasing the effectiveness and efficiency of software development with particular emphasis on requirements specifications.

952 Knowledge-Based Systems Applications (3:3:0).Prerequisite: CS 580 or INFS 650. An analysis of the framework of applications of knowledge-based systems within information technology. The impact of KSS on systems such as computer integrated manufacturing, planning support systems, and distributed information systems is studied. Procedural and nonprocedural computer languages are compared in support of decision processes in large-scale systems.

958 Basic and Applied Decision Support Systems Technology (3:3:0).Prerequisite: SYST 642. An analysis of tools, techniques, and methods that contribute to the design, development, application, and evaluation of interactive computer-based decision support systems. State of the art and state of the expectation of basic and applied decision support systems technologies like requirements definition, software engineering, analytical methods assessment, and structured evaluation are analyzed.

960 Expert Database Systems (3:3:0).Prerequisites: CS 580 and INFS 614. A study of the concepts, tools, techniques, and architectures of expert database systems, which support the specification, design, prototyping, production and maintenance of applications requiring knowledge-directed processing of shared information stored in large databases.

961 Topics in Distributed Database Management (3:3:0).Prerequisite: INFT 861 or permission of instructor. Current topics of advanced research in distributed database management. Topics include transaction management, concurrency control, deadlocks, replicated data management, query processing, and reliability.

962 Advanced Topics in Computer Security (3:3:0).Prerequisite: INFT 862 or 865, or permission of instructor. Current topics of advanced research in computer security. Content varies depending on faculty interests, research developments, and student demand. The seminar format requires substantial student participation. Representative topics include formal models for computer security, multilevel data models, multilevel database management system architectures, secure concurrency control protocols, distributed secure system architectures, integrity models and mechanisms, security policy, and requirements analysis.

972/CSI 972 Mathematical Statistics I (3:3:0).Prerequisite: STAT 652 or equivalent. A focus on the theory of estimation. The principles of estimation are explored, including the method of moments, least squares, maximum likelihood, and maximum entropy methods. The methods of minimum variance unbiased estimation are covered in detail. Topics include sufficiency and completeness of statistics, Fisher information, Cramer-Rao bounds, Bhattacharyya bounds, asymptotic consistency and distributions, statistical decision theory, minimax and Bayesian decision rules, and applications to engineering and scientific problems.

973/CSI 973 Mathematical Statistics II (3:3:0).Prerequisite: INFT 972. Continuation of INFT 972. A concentration on the theory of hypothesis testing. Topics include characterizing the decision process, simple versus simple hypothesis tests, Neyman-Pearson Lemma, uniformly most powerful tests, unbiasedness of tests, invariance of tests, randomized tests, and sequential tests. Applications of the testing principles are made to situations in the normal distribution family and to other families of distributions.

976/CSI 976 Statistical Inference for Stochastic Processes (3:3:0).Prerequisite: INFT 746/CSI 776. The modern theory of parameter estimation and hypothesis testing for stochastic processes, counting processes with random intensities, and solutions to stochastic differential equations driven by martingales. Applications to engineering, biology, and economics are considered.

978/CSI 978 Statistical Analysis of Signals (3:3:0).Prerequisites: STAT 544 and 658 or equivalent. An advanced course in the analysis of discrete- and continuous-time signals using methods of stochastic differential equations and time series. Familiarity with the methods of harmonic analysis and times series modeling is presumed. Topics include state-space modeling and eigen-value processing, nonlinear modeling of signals, non-Gaussian stochastic process structure, detection and estimation of vector-valued signals, robust signal detection, with applications to array processing, and target tracking.

979/CSI 979 Topics in Statistical Aspects of Information Technology (3:3:0). Prerequisite: STAT 652 or equivalent. A study of statistical science--the body of methods and techniques that convert raw data into information. Contents vary. Such topics as high-interaction statistical graphics, stochastic methods for parallel computing, cryptography and covert communications, order-restricted inference, treatments of imprecision, and the foundations of inference are covered. May be repeated when topics are distinctly different.

980 Advanced Topics in Applied Probability (3:3:0).Prerequisite: OR 645, 647, or permission of instructor depending on the topic(s) for the semester. Special topics and recent developments in the field of applied probability. Contents vary and possible topics include computational probability, stochastic point processes, advanced queueing theory, traffic and transportation models, percolation, processes of random aggregation and coagulation, and Markov decision processes. May be repeated for credit when topics are distinctly different.

981 Advanced Topics in Optimization (3:3:0).Prerequisite: INFT 741 or 750 or 881 or 882 or 884. Special topics and recent developments in optimization theory and computation. Contents vary and may include topics in linear, nonlinear, combinatorial, network, global, or stochastic optimization. The course prepares students to perform research in optimization, and requires active student participation. May be repeated for credit when topics are distinctly different.

983 Advanced Topics in Network Optimization (3:3:0).Prerequisite: OR 643. Recent developments in solving optimization problems on networks. The course prepares doctoral students to perform advanced research on network-related problems. Topics include linear, discrete, nonlinear, and stochastic problems. Several aspects of these problems are also studied. These include but are not limited to computational complexity, exact algorithms, heuristics, solvable special cases, and computer implementation issues.

990 Dissertation Topic Presentation (1:0:0).Prerequisite: Completion of all course requirements for Ph.D. in INFT or permission of instructor. An opportunity for Ph.D. Students to present their research proposal for critique to interested faculty and students. The course covers the presentation of the research topic for the Ph.D. in Information Technology, and is required of all Ph.D. Students. At the end of the course, the student will have completed the dissertation research proposal. May be repeated with a change in topic, although degree credit is given once.

998 Doctoral Dissertation Proposal (1-12:0:0). Work on a research proposal that forms the basis for a doctoral dissertation. May be repeated. No more than 24 credits hours of INFT 998 and 999 may be applied to doctoral degree requirements.

999 Doctoral Dissertation (1-12).Prerequisite: Admission to candidacy. A formal record of commitment to doctoral dissertation research under the direction of a faculty member in information technology. May be repeated as needed.