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ENG EC 505: Stochastic Processes
Undergraduate Prerequisites: ENG EC 401 and CAS MA 142; or equivalent and either ENGEK381 or ENGEK500.
Introduction to discrete and continuous-time random processes. Correlation and power spectral density functions. Linear systems driven by random processes. Optimum detection and estimation. Bayesian, Weiner, and Kalman filtering.
ENG EC 508: Wireless Communication
Undergraduate Prerequisites: ENG EK 381.
Fundamentals of wireless communication from a physical layer perspective. Multipath signal propagation and fading channel models. Design of constellations to exploit time, frequency, and spatial diversity. Reliable communication and single-user capacity. Interference management, multiple-access protocols, and multi-user capacity. Cellular uplink and downlink. Multiple-antenna systems and architectures. Connections to modern wireless systems and standards.
ENG EC 512: Enterprise Client-Server Software Systems Design
Undergraduate Prerequisites: Senior standing or consent of instructor, programming experience in C++, Java, or C#, basic knowledge of internet protocols and HTML, ENGEC440 or equivalent is required. ENGEC441 ENGEC447 are recommen
Examination of past, current, and emerging technologies. Client side technologies including DHTML, CSS, scripting, ActiveX, RSS, and proprietary applications. Legacy server side technologies including CGI, ISAPL, and active server pages. Current and emerging server technologies including ASP.NET 2, XML/SOAP web services, wireless and handheld access, WAP/WML, SQL databases, streaming media, CMS, and middleware. Design and implementation of solutions involving database connectivity, session state, security requirements, SSL, and authentication of clients. Small-team projects involving design through implementation.
ENG EC 513: Computer Architecture
Undergraduate Prerequisites: ENG EC 413 or ENG EC 605; Or instructor consent
Graduate Prerequisites: ENG EC 413 and ENG EC 605; Or instructor consent
Computer architecture and design. Topics include computer arithmetic and ALU design; performance evaluation; instruction set design; CPU design, including pipelining, branch prediction, and speculative execution; memory hierarchy, including cache basics, cache design for performance, and virtual memory support; I/O, including devices, interfaces, specification, and modeling. Examples from high-end microprocessors and embedded systems.
ENG EC 515: Digital Communication
Undergraduate Prerequisites: ENG EC 415; And ENGEC381 or ENGEK381
Canonical point-to-point digital communication problem; Communication channel models; Optimal receiver principles with focus on additive Gaussian noise channels: Maximum Aposteriori Probability (MAP) and Maximum Likelihood (ML) receivers for both vector and waveform channels, principles of irrelevance and reversibility; Concepts of signal space and signal constellation; Efficient signaling for message sequences over frequency-flat additive Gaussian noise channels: basic digital modulation and demodulation techniques and their performance analysis; Notions of symbol and bit rate, symbol and bit error probability, and power and bandwidth efficiency; Real passband additive Gaussian noise waveform channels and their equivalent complex base-band representation; Efficient signaling for message sequences over general bandlimited additive Gaussian noise channels: signal design and equalization methods to combat intersymbol interference; Coherent versus Noncoherent digital signaling; Synchronization; Channel estimation; Error correction coding basics.
ENG EC 516: Digital Signal Processing
Undergraduate Prerequisites: ENG EC 401; And ENGEC381 or ENGEK381
Advanced structures and techniques for digital signal processing and their properties in relation to application requirements such as real-time, low-bandwidth, and low-power operation. Optimal FIR filter design; time-dependent Fourier transform and filterbanks; Hilbert transform relations; cepstral analysis and deconvolution; parametric signal modeling; multidimensional signal processing; multirate signal processing.
ENG EC 517: Introduction to Information Theory
Undergraduate Prerequisites: ENG EK 381.
Discrete memoryless stationary sources and channels; Information measures on discrete and continuous alphabets and their properties: entropy, conditional entropy, relative entropy, mutual information, differential entropy; Elementary constrained convex optimization; Fundamental information inequalities: data-processing, and Fano's; Block source coding with outage: weak law of large numbers, entropically typical sequences and typical sets, asymptotic equipartition property; Block channel coding with and without cost constraints: jointly typical sequences, channel capacity, random coding, Shannon's channel coding theorem, introduction to practical linear block codes; Rate-distortion theory: Shannon's block source coding theorem relative to a fidelity criterion; Source and channel coding for Gaussian sources and channels and parallel Gaussian sources and channels (water-filling and reverse water-filling); Shannon's source-channel separation theorem for point-to-point communication; Lossless data compression: Kraft's inequality, Shannon's lossless source coding theorem, variable-length source codes including Huffman, Shannon-Fano-Elias, and Arithmetic codes; Applications; Mini course-project.
ENG EC 519: Speech Processing by Humans and Machines
Undergraduate Prerequisites: ENG EK 381; ENGBE401 or ENGEC401 and MATLAB
Speech (naturally spoken) is the main mode of communication between humans. Speech technology aims at providing the means for speech-controlled man-machine interaction. The goal of this course is to provide the basic concepts and theories of speech production, speech perception, and speech signal processing. The course is organized in a manner that builds a strong foundation of basics, followed by a range of signal processing methods for representing and processing the speech signal. 4 cr.
ENG EC 520: Digital Image Processing and Communication
Undergraduate Prerequisites: ENG EC 416 and ENG EK 381; ENGEK381 or ENGEC381 or equivalents
Review of signals and systems in multiple dimensions. Sampling of still images. Quantization of image intensities. Human visual system. Image color spaces. Image models and transformations. Image enhancement and restoration. Image analysis. Image compression fundamentals. Image compression standards (JPEG, JPEG-2000). Homework will include MATLAB assignments.
ENG EC 521: Cybersecurity
Undergraduate Prerequisites: ENG EC 327.
Fundamentals of security related to computers and computer networks. Laws and ethics. Social engineering and psychology-based attacks. Information gathering, network mapping, service enumeration, and vulnerability scanning. Operating system security related to access control, exploits, and disk forensics. Shellcoding. Wired and wireless network security at the physical, network, and application layers. Theoretical lessons are augmented with case studies and demonstrative experimental labs.
ENG EC 524: Optimization Theory and Methods
Undergraduate Prerequisites: ENG EK 102 or CAS MA 142 or ENG EK 103.
Introduction to optimization problems and algorithms emphasizing problem formulation, basic methodologies, and underlying mathematical structures. Classical optimization theory as well as recent advances in the field. Topics include modeling issues and formulations, simplex method, duality theory, sensitivity analysis, large-scale optimization, integer programming, interior-point methods, non-linear programming optimality conditions, gradient methods, and conjugate direction methods. Applications are considered; case studies included. Extensive paradigms from production planning and scheduling in manufacturing systems. Other illustrative applications include fleet management, air traffic flow management, optimal routing in communication networks, and optimal portfolio selection. Meets with ENGSE524. Students may not receive credit for both.
ENG EC 527: High Performance Programming with Multicore and GPUs
Considers theory and practice of hardware-aware programming. Key theme is obtaining a significant fraction of potential performance through knowledge of the underlying computing platform and how the platform interacts with programs. Studies architecture of, and programming methods for, contemporary high-performance processors. These include complex processor cores, multicore processors, and graphics processors. Laboratory component includes use and evaluation of programming methods on these processors through applications such as matrix operations and the Fast Fourier Transform.
ENG EC 528: Cloud Computing
Undergraduate Prerequisites: ENG EC 327 and ENG EC 330; Undergrads must have taken EC327 or equivalent and preferably anothersoftware course, EC330 or EC440, before taking this course.
Graduate Prerequisites: ENG EC 504; Graduate students must have taken a rigorous programming class recently, such as EC504 or equivalent (or have major software design experience in industry).
Fundamentals of cloud computing covering IaaS platforms, OpenStack, key Big Data platforms, and data center scale systems. Examines influential publications in cloud computing. Culminates in a group project supervised by a mentor from industry or academia.
ENG EC 533: Advanced Discrete Mathematics
Undergraduate Prerequisites: CAS MA 124; or equivalent
Selected topics in discrete mathematics. Formal systems. Mathematical deduction. Logical concepts. Theorem proving. Sets, relations on sets, operations on sets. Functions, graphs, mathematical structures, morphisms, algebraic structures, semigroups, quotient groups, finite-state machines, their homomorphism, and simulation. Machines as recognizers, regular sets. Kleene theorem.
ENG EC 535: Introduction to Embedded Systems
Undergraduate Prerequisites: ENG EC 311 or ENG EC 327 or ENG EC 605; or equivalent; basic knowledge of assembly languages, computer organization and logic circuits, basic knowledge of data structure and algorithms, programming skills in C/C++.
Graduate Prerequisites: ENG EC 311 or ENG EC 327 or ENG EC 605; or equivalent; basic knowledge of assembly languages, computer organization and logic circuits, basic knowledge of data structure and algorithms, programming skills in C/C++.
This course introduces students to a unified view of hardware and software in embedded systems. The lectures will survey a comprehensive array of techniques including system specification languages, embedded computer architecture, real-time operating systems, hardware-software codesign, and co-verification techniques. The lectures will be complemented by assignments and projects that involve system design, analysis, optimization, and verification.
ENG EC 541: Computer Communication Networks
Undergraduate Prerequisites: ENG EC 441.
Basic delay and blocking models for computer communications: M/M/1 queue; Jackson networks and loss networks; analysis of MAC protocols; flow control for data traffic; TCP and active queueing mechanisms for congestion control; traffic shaping and network calculus; packet switch architectures and scheduling algorithms; routing algorithms; flow assignment and fairness.
ENG EC 543: Sustainable Power Systems: Planning, Operation and Markets
Undergraduate Prerequisites: Graduate/Senior status and consent of instructor.
Breakthroughs in clean energy generation technologies and the advantage of exploiting efficiently the available work in fossil fuels will render electricity the dominant energy form in a sustainable environment future. We review the key characteristics of Electric Power Transmission and Distribution (T&D) networks and the associated planning and operation requirements that ensure supply adequacy, system security and stability. Capital asset investment and operation cost minimization is discussed in a systems engineering context where the assets as well as the dynamic behavior of generators, T&D networks, and loads interact. Recent developments in the formation of competitive wholesale markets at the High Voltage Transmission system level, the associated market participation and clearing rules and the market clearing optimization algorithms are presented and analyzed in terms of their effectiveness in fostering cost reflective price signals and competitive conditions that encourage optimal distributed/not-centralized investment and operating decisions. Finally, we present T&D congestion and supply-demand imbalance related barriers to the widespread adoption of environmentally friendly and economically efficient technological breakthroughs, and propose a systems engineering and real-time retail-market based coordination of centralized as well as decentralized generation, storage and load management resources that is able to achieve desirable synergies and mitigate these barriers. 4 cr
ENG EC 544: Networking the Physical World
Undergraduate Prerequisites: ENG EC 312 or ENG EC 450; ENG EC 441 is desirable, C programming experience required.
Considers the evolution of embedded network sensing systems with the introduction of wireless network connectivity. Key themes are computing optimized for resource constrained (cost, energy, memory and storage space) applications and sensing interfaces to connect to the physical world. Studies current technology for networked embedded network sensors including protocol standards. A laboratory component of the course introduces students to the unique characteristics of distributed sensor motes including programming, reliable communication, sensing modalities, calibration, and application development. Meets with ENGME544. Students may not receive credit for both.
ENG EC 551: Advanced Digital Design with Verilog and FPGA
Undergraduate Prerequisites: ENG EC 311 and ENG EC 413; or ENGEC605 or instructor consent
Content includes use of HDL (Verilog) for design, synthesis and simulation, and principles of register transfer level (RTL). Programmable logic, such as field programmable gate array (FPGA) devices, has become a major component of digital design. In this class the students learn how to write HDL models that can be automatically synthesized into integrated circuits such as FPGA. Laboratory and homework exercises include writing HDL models of combinational and sequential circuits, synthesizing models, performing simulation, and fitting to an FPGA by using automatic place and route. The course has lab orientation and is based on a sequence of Verilog design examples.
ENG EC 555: Introduction to Biomedical Optics
Undergraduate Prerequisites: ENG BE 200 and CAS MA 226; ENG BE 200 or equivalent. CAS MA 226 and BE/EC 401
This course surveys the applications of optical science and engineering to a variety of biomedical problems, with emphasis on optical and photonics technologies that enable real, minimally-invasive clinical and laboratory applications. The course teaches only those aspects of the biology itself that are necessary to understand the purpose of the applications. The first weeks introduce the optical properties of tissue, and following lectures cover a range of topics in three general areas: 1) Optical spectroscopy applied to diagnosis of cancer and other tissue diseases; 2) Photon migration and diffuse optical imagine of subsurface structures in tissue; and 3) laser-tissue interactions and other applications of light for therapeutic purposes. Some classes will invoke traditional lectures, and others will be "inverted," devoted to discussing and understanding application problems, with students having read textbook sections or online material prior to class.