Electrical and Computer Engineering
101.
Introduction to Electrical and Computer Engineering.
(1)
Insight into electrical engineering is gained through videos, “hands-on” experiments, use of computer software to learn basic problem-solving skills and a team-oriented design project.
131.
Programming Fundamentals.
(3)
Fundamental programming concepts, including consideration of abstract machine models with emphasis on the memory hierarchy, basic programming constructs, functions, parameter passing, pointers and arrays, file I/O, bit-level operations and interfacing to external devices.
203.
Circuit Analysis I.
(3)
Basic elements and sources. Energy and power. Ohm's law and Kirchhoff's laws. Resistive networks, node and loop analysis. Network theorems. First-order and second-order circuits. Sinusoidal sources and complex representations: impedance, phasors, complex power. Three-phase circuits.
Prerequisite: ECE 131 and MATH 163. Pre- or Corequisite: MATH 316 and PHYC 161.
206L.
Instrumentation.
(2)
Introduction to laboratory practices and the use of test equipment. Measurements on basic electrical components, dc and ac circuits using ohmmeters, voltmeters, ammeters and oscilloscopes. Circuit simulation.
Prerequisite: 203 and ENGL 102
213.
Circuit Analysis II.
(3)
General transient analysis of electrical circuits. Laplace transform with applications to circuit analysis. State-space equations. Fourier series analysis. The network function; convolution; frequency response.
Prerequisite: 203 and MATH 316 Corequisite: MATH 314
231.
Intermediate Programming and Engineering Problem Solving.
(3)
Introducton to elementary data structures, program design and computer-based solution of engineering problems. Topics include use of pointers, stacks, queues, linked lists, trees, graphs, systems and device-level programming and software design methodology.
Prerequisite: ECE 131
238L.
Computer Logic Design.
(4)
Binary number systems. Boolean algebra. Combinational, sequential and register transfer logic. VHDL. Arithmetic/logic unit. Memories, computer organization. Input-output. Microprocessors.
Prerequisite: ECE 131
**314.
Signals and Systems.
(3)
Continuous and discrete time signals and systems; time and frequency domain analysis of LTI systems, Fourier series and transforms, discrete time Fourier series/transform sampling theorem, block diagrams, modulation/demodulation, filters.
Prerequisite: 213 and MATH 264
**322L.
Electronics II.
(4)
Analysis, design, and characterization of linear circuits including operational amplifiers. Design of biasing and reference circuits, multistage amplifiers, and feedback circuits.
Prerequisite: 321L
**321L.
Electronics I.
(4)
Introduction to diodes, bipolar and field-effect transistors. Analysis and design of digital circuits, gates, flip-flops and memory circuits. Circuits employing operational amplifiers. Analog to digital and digital to analog converters.
Prerequisite: 213
330.
Software Design.
(3)
Design of software systems using modern modeling techniques. Relationship between software design and process, with emphasis on UML and its interface application code. Exposure to design patterns, software frameworks, and software architectural paradigms.
Prerequisite: 231
**331.
Data Structures and Algorithms.
(3)
An introduction to data structures and algorithms. Topics include asymptotic notation recurrence relations, sorting, hash tables, basic priority queues, balanced search trees and basic graph representation and search.
Prerequisite: 231 and MATH 327 Corequisite: 340
**335.
Integrated Software Systems.
(3)
Course considers design principles, implementation issues, and performance evaluation of various software paradigms in an integrated computing environment. Topics include performance measurement and evaluation, program optimization for the underlying architecture, integration and security for large-scale software systems.
Prerequisite: 330 and 337
**337.
Introduction to Computer Architecture and Organization.
(3)
Survey of various levels of computer architecture and design; microprogramming and processor architecture, assembly language programming, operating system concepts and input/output via the operating system. Three lectures, 1 hr. lab.
Prerequisite: 231 and 238L
{Spring}
**338.
Intermediate Logic Design.
(3)
Advanced combinational circuits; XOR and transmission gates; computer-based optimization methods; RTL and HDL; introduction to computer aided design; advanced sequential machines; asynchronous sequential machines; timing issues; memory and memory interfacing; programmable logic devices; and VLSI concepts.
Prerequisite: 238L
**340.
Probabilistic Methods in Engineering.
(3)
Introduction to probability, random variables, random processes, probability distribution/density functions, expectation correlation, power spectrum, WSS processes, confidence internals, transmission through LIT systems, applications of probability.
Prerequisite: MATH 314
**344L.
Microprocessors.
(4)
Computers and Microprocessors: architecture, assembly language programming, input/output and applications.
Prerequisite: 206L and 238L and 321L
Three lectures, 3 hours lab.
345 .
Introduction to Control Systems.
(3)
Introduction to the feedback control problem. Plant modeling, transfer function and state-space descriptions. Stability criteria. Nyquist and root-locus design. Introduction to analytical design. Z-transforms and digital control. Laboratory design project.
Prerequisite: 314
**360.
Electromagnetic Fields and Waves.
(3)
Maxwell’s equations, plane wave propagation, waveguides and transmission lines, transient pulse propagation and elementary dipole antenna.
Prerequisite: 213 and PHYC 161 and MATH 264
**371.
Materials and Devices.
(3 to a maximum of 6 ? [3])
Introduction to quantum mechanics, crystal structures, insulators, metals, and semiconductor material properties, bipolar, field effect and light emitting devices.
Prerequisite: PHYC 262
412.
Introduction to Computer Graphics: Scanline Algorithms.
(3)
(Also offered as CS 412)
This course is an introduction to the technical aspects of raster algorithms in computer graphics. Students will learn the foundational concepts of 2-D and 3-D graphics as they relate to real-time and offline techniques. Students will develop a video game as a final project to demonstrate the algorithms learned in class.
Prerequisite: 331 or CS 361L
{Fall}
413.
Introduction to Ray and Vector Graphics.
(3)
(Also offered as CS 413)
Topics include ray-geometry intersections, viewing, lenses, local/global illumination, procedural textures/models, spline curves and surfaces, and statistical integration for realistic image synthesis. Students will write a raytracing renderer from scratch, exploring high performance implementations and realistic rendering.
Prerequisite: CS 361L or ECE 331
419.
Senior Design I.
(3)
Design methodology and development of professional project oriented skills including communication, team management, economics and engineering ethics. Working in teams, a proposal for a large design is prepared in response to an industrial or in-house sponsor.
Restriction: ECE major and senior standing
420.
Senior Design II.
(3)
Continuation of 419. Students work in assigned teams to implement proposal developed in 419. Prototypes are built and tested to sponsor specifications, and oral and written reports made to the project sponsor.
Prerequisite: 419
421 / 523.
Analog Electronics.
(3)
Design of advanced analog electronic circuits. BJT and MOSFET operational amplifiers, current mirrors and output stages. Frequency response and compensation. Noise. A/D and D/A converters.
Prerequisite: 322L
*424.
Digital VLSI Design.
(3)
CMOS logic gates and circuits, transistor implementations, applications to sequential circuits, VLSI data path and controller design, VLSI routing issues and architectures, RTL and VLSI impacts and applications to microprocessor design.
Prerequisite: 321L and 338
*432.
Introduction to Parallel Processing.
(3)
(Also offered as CS 442)
Machine taxonomy and introduction to parallel programming. Performance issues, speed-up and efficiency. Interconnection networks and embeddings. Parallel programming issues and models: control parallel, data parallel and data flow. Programming assignments on massively parallel machines.
Prerequisite: (331 or CS 351L) and (337 or CS 341L)
**435.
Software Engineering.
(3)
Management and technical issues including business conduct and ethics related to the design of large engineering projects. Student teams will address the design, specification, implementation, testing and documentation of a large hardware/software project.
Prerequisite: 331 and 335
*437.
Computer Operating Systems.
(3)
(Also offered as CS 481)
Fundamental principles of modern operating systems design, with emphasis on concurrency and resource management. Topics include processes, interprocess communication, semaphores, monitors, message passing, input/output device, deadlocks memory management, files system design.
Prerequisite: (330 and 337) or CS 341L
*438.
Design of Computers.
(3)
Computer architecture; design and implementation at HDL level; ALU, exception handling and interrupts; addressing; memory; speed issues; pipelining; microprogramming; introduction to distributed and parallel processing; buses; bus protocols and bus masters. CAD project to include written and oral presentations.
Prerequisite: 337 and 338 and 344L
*439.
Introduction to Digital Signal Processing.
(3)
Bilateral Z transforms, region of convergence, review of sampling theorem, aliasing, the discrete Fourier transform and properties, analysis/design of FIR/IIR filters, FFT algorithms spectral analysis using FFT.
Prerequisite: 314
*440.
Introduction to Computer Networks.
(3)
(Also offered as CS 485)
Theoretical and practical study of computer networks, including network structures and architectures. Principles of digital communications systems. Network topologies, protocols and services. TCP/IP protocol suite. Point-to-point networks; broadcast networks; local area networks; routing, error and flow control techniques.
Prerequisite: 330 and 337 Corequisite: 340
*441.
Introduction to Communication Systems.
(3)
Amplitude/frequency modulation, pulse position/amplitude modulation, probabilistic noise model, AWGN, Rice representation, figure of merit, phase locked loops, digital modulation, introduction to multiple access systems.
Prerequisite: 314 and 340
*442.
Introduction to Wireless Communications.
(3)
The course is an introduction to cellular telephone systems and wireless networks, drawing upon a diversity of electrical engineering areas. Topics include cellular concepts, radio propagation, modulation methods and multiple access techniques.
Prerequisite: 314 and 360
*443.
Hardware Design with VHDL.
(3)
The VHDL hardware description language is used for description of digital systems at several levels of complexity, from the system level to the gate level. Descriptions provide a mechanism for documentation, for simulation and for synthesis.
Prerequisite: 338
*446.
Design of Feedback Control Systems.
(3)
Modeling of continuous and sampled-data control systems. State-space representation. Sensitivity, stability and optimization of control systems. Design of compensators in the frequency and time domains. Phase-plane, describing function design for non-linear systems, and laboratory design project.
Prerequisite: 345
448 / 548.
Fuzzy Logic with Applications.
(3)
Theory of fuzzy sets; foundations of fuzzy logic. Fuzzy logic is shown to contain evidence, possibility and probability logics; course emphasizes engineering applications; control, pattern recognition, damage assessment, decisions; hardware/software demonstrations.
456 / 556.
Entrepreneurial Engineering.
(3)
(Also offered as ME 456)
Review and application of necessary elements for successfully launching technical businesses; focuses upon technology, manufacturing, management, marketing, legal and financial aspects. Students work in groups developing elements of new businesses and producing business plans.
Restriction: senior standing
460 / 560.
Introduction to Microwave Engineering.
(3)
This lecture/laboratory course provides essential fundamentals for rf, wireless and microwave engineering. Topics include: wave propagation in cables, waveguides and free space; impedance matching, standing wave ratios, Z- and S- parameters.
Prerequisite: 360
*463.
Advanced Optics I.
(3)
(Also offered as PHYC 463)
Electromagnetic theory of geometrical optics, Gaussian ray tracing and matrix methods, finite ray tracing, aberrations, interference and diffraction.
Prerequisite: PHYC 302
*464.
Laser Physics .
(3)
(Also offered as PHYC 464)
Resonator optics. Rate equations; spontaneous and stimuated emission; gas, semiconductor and solid state lasers, pulsed and mode-locked laser techniques.
Prerequisite: 360 or PHYC 406
469 / 569.
Antennas for Wireless Communication Systems.
(3)
Aspects of antenna theory and design; radiation from dipoles, loops, apertures, microstrip antennas and antenna arrays.
Prerequisite: 360
*471.
Materials and Devices II.
(3)
An intermediate study of semiconductor materials, energy band structure, p-n junctions, ideal and non-ideal effects in field effect and bipolar transistors.
Prerequisite: 360 and 371
474L / 574L.
Microelectronics Processing.
(3)
Fledderman, Hersee
(Also offered as NSMS 574L)
Materials science of semiconductors, microelectronics technologies, device/circuit fabrication, parasitics and packaging. Lab project features small group design/fabrication/testing of MOS circuits.
*475.
Introduction to Electro-Optics and Opto-Electronics.
(3)
Basic electro-optics and opto-electronics, with engineering applications. Interaction of light with matter. Introduction to optics of dielectrics, metals and crystals. Introductory descriptions of electro-optic, acousto-optic and magneto-optic effects and related devices. Light sources, displays and detectors. Elementary theory and applications of lasers, optical waveguides and fibers.
Prerequisite: 371
486 / 586.
Design for Manufacturability.
(3)
(Also offered as ME 486)
Introduction to methods of design for manufacturability. Emphasis is on teamwork and designing to your customer’s needs. This is achieved through statistical methods and computer based systems.
Restriction: senior standing
*487.
Semiconductor Factory Design and Operations.
(3)
A detailed overview of the operations of an integrated circuit fabrication facility using Sandia’s Microelectronics Development Laboratory as a prototype. Topics include building facilities, equipment, software tracking and personnel.
490.
Internship.
(3)
Professional practice under the guidance of a practicing engineer. Assignments include design or analysis of systems or hardware, or computer programming. A preliminary proposal and periodic reports are required. The engineer evaluates student’s work; a faculty monitor assigns grade.
Restriction: ECE major and junior standing. (12 hours/week) (24 hours/week in summer session).
Offered on a CR/NC basis only.
491.
Undergraduate Problems.
(1-6 to a maximum of 6 ?)
Registration for more than 3 hours requires permission of department chairperson.
493.
Honors Seminar.
(1-3)
A special seminar open only to honors students. Registration requires permission of department chairperson.
494.
Honors Individual Study.
(1-6)
Open only to honors students.
Registration requires permission of the department chairperson and of the supervising professor.
495 / 595.
Special Topics.
(1-4 to a maximum of 9, 1-4 to a maximum of 15 ?)
Restriction: ECE major and senior standing.
500.
Theory of Linear Systems.
(3)
State space representation of dynamical systems. Analysis and design of linear models in control systems and signal processing. Continuous, discrete and sampled representations. This course is fundamental for students in the system areas.
506.
Optimization Theory.
(3)
Introduction to the topic of optimization by the computer. Linear and nonlinear programming. The simplex method, Karmakar method, gradient, conjugate gradient and quasi-Newton methods, Fibonacci/Golden search, Quadratic and Cubic fitting methods, Penalty and Barrier methods.
509.
Parallel Algorithms.
(3)
(Also offered as CS 509)
Design and analysis of parallel algorithms using the PRAM model, with emphasis on graph algorithms, searching and sorting, and linear algebra applications. Embedding into hypercubic and related networks. Introduction to parallel complexity theory.
Prerequisite: 537
510.
Medical Imaging.
(3)
This course will introduce the student to medical imaging modalities (e.g. MRI, Nuclear Imaging, Ultrasound) with an emphasis on a signals and systems approach. Topics will include hardware, signal formation, image reconstruction and application.
512.
Advanced Image Synthesis.
(3)
(Also offered as CS 512)
Covers image synthesis techniques from perspective of high-end scanline rendering, including physically-based rendering algorithms. Topics: radiometry, stochastic ray tracing, variance reduction, photon mapping, reflection models, participating media, advanced algorithms for light transport.
513.
Real-Time Rendering and Graphics Hardware.
(3)
(Also offered as CS 513)
Course covers advanced algorithms in real-time rendering and graphics hardware, bringing students up to speed with cutting edge real-time graphics. Topics: advanced GPU algorithms for graphics and non-graphics applications. Term project required
514.
Nonlinear and Adaptive Control.
(3)
Linearization of nonlinear systems. Phase-plane analysis. Lyapunov stability analysis. Hyperstability and Popov stability criterion. Adaptive control systems. Adaptive estimation. Stability of adaptive control systems, backstepping and nonlinear designs.
Prerequisite: 500
515.
Scientific and Information Visualization.
(3)
(Also offered as CS 515)
Introduction to scientific and data visualization techniques. Topics: data manipulation, feature extraction, visual display, peer critique of project design, data formats and sampling, geometric extraction, volume visualization, flow visualization, abstract data visualization, user interaction techniques
516.
Computer Vision.
(3)
(Also offered as CS 532)
Theory and practice of feature extraction, including edge, texture and shape measures. Picture segmentation; relaxation. Data structures for picture description. Matching and searching as models of association and knowledge learning. Formal models of picture languages.
517.
Pattern Recognition.
(3)
(Also offered as CS 531)
Decision functions and dichotomization; prototype classification and clustering; statistical classification and Bayes theory; trainable deterministic and statistical classifiers. Feature transformations and selection.
518.
Synthesis of Nanostructures.
(3)
Brinker, Brueck
(Also offered as CHNE, NSMS 518)
Underlying physical and chemical principles (optics, organic and inorganic chemistry, colloid chemistry, surface and materials science) for nanostructure formation using ‘top-down’ lithography (patterned optical exposure of photosensitive materials) and ‘bottom-up’ self-assembly. Labs will synthesize samples.
Prerequisite: NSMS 510
{Spring}
519.
Theory, Fabrication, and Characterization of Nano & Microelectromechanical Systems (NEMS/MEMS).
(3)
(Also offered as ME, NSMS 519)
Lectures and laboratory projects on physical theory, design, analysis, fabrication, and characterization of micro and nanosystems. Special attention given to scaling effects involved with operation of devices at nano and microscale.
520.
VLSI Design.
(3)
Advanced topics include: lC technologies, CAD tools, gate arrays, standard cells and full custom designs. Design of memories, PLA, I/0 and random logic circuit. Design for testability.
523 / 421.
Analog Electronics.
(3)
Design of advanced analog electronics circuits. BJT and MOSFET operational amplifiers, current mirrors and output stages. Frequency response and compensation. Noise. A/D and D/A converters.
524.
Collaborative Interdisciplinary Teaching.
(3)
(Also offered as ANTH 624, BIOL 524, CS 524, STAT 524)
Course designed to develop the methods content and assessment of effective interdisciplinary biological courses; Students will develop and teach an undergraduate interdisciplinary topics course. Topics vary.
Restriction: permission of instructor
528.
Embedded Systems Architecture.
(3)
Development and analysis of techniques and algorithms for use in embedded processor systems. Application of tools implementing solutions to control and data applications involving standard processing paradigms and programmable logic systems.
531.
Error-Correcting Codes.
(3)
Efficient insertion of redundant bits into binary data for protection against error; association with linear algebra; sequential coding and decoding logic; arithmetic codes for computational circuits.
532.
Nanoscale Electronic and Photonic Devices.
(3)
Huffaker
(Also offered as NSMS 532)
Introduces devices, device physics, characteristics and possible applications specific to the nanoscale. Topics include single electron transistor, carbon nanotube electronics, quantum dot devices, spin-polarized electronic and photonic devices.
533.
Digital Image Processing.
(3)
Fundamentals of 2D signals and systems. Introduction to multidimensional signal processing. Applications in digital image processing. Image formation, representation and display. Linear and nonlinear operators in multiple dimensions. Orthogonal transforms representation and display. Image analysis, enhancement, restoration and coding. Students will carry out image processing projects.
534.
Plasma Physics I.
(3)
(Also offered as PHYC 534)
Plasma parameters, adiabatic invariants, orbit theory, plasma oscillations, hydromagnetic waves, plasma transport, stability, kinetic theory, nonlinear effects, applications.
536.
Computer System Software.
(3)
Course considers design principles, implementation issues and performance evaluation of system software in advanced computing environments. Topics include resource allocation and scheduling, information service provider and manipulation, multithreading and concurrency, security for parallel and distributed systems.
537.
Foundations of Computing.
(3)
Computational aspects of engineering problems. Topics include machine models and computability, classification and performance analysis of algorithms, advanced data structures, approximation algorithms, introduction to complexity theory and complexity classes.
538.
Advanced Computer Architecture.
(3)
Course provides an in-depth analysis of computer architecture techniques. Topics include high speed computing techniques, memory systems, pipelining, vector machines, parallel processing, multiprocessor systems, high-level language machines and data flow computers.
539.
Digital Signal Processing.
(3)
Hilbert spaces, orthogonal basis, generalized sampling theorem, multirate systems, filterbanks, quantization, structures for LTI systems, finite word-length effects, linear prediction, min/max phase systems, multiresolution signal analysis.
540.
Advanced Networking Topics.
(3)
Research, design and implementation of high-performance computer networks and distributed systems. High speed networking technologies, multimedia networks, enterprise network security and management, client/server database applications, mobile communications and state-of-the-art internetworking solutions.
541.
Probability Theory and Stochastic Processes.
(3)
Axiomatic probability theory, projection theorem for Hilbert spaces, conditioned expectations, modes of stochastic convergence, Markov chains, mean-square calculus, Wiener filtering, optimal signal estimation, prediction stationarity, ergodicity, transmission through linear and nonlinear systems, sampling.
542.
Digital Communication Theory.
(3)
Elements of information theory and source coding, digital modulation techniques, signal space representation, optimal receivers for coherent/non-coherent detection in AWGN channels, error probability bounds, channel capacity, elements of block and convolutional coding, fading, equalization signal design.
Prerequisite: 541
545.
Digital Control Systems.
(3)
Discrete-time signals and systems. Performance and stability criteria. Design approaches for digital control of analog plants. Sampling and signal quantization. Optimal and adaptive control. Microprocessor implementation of digital control algorithms.
Prerequisite: 500
546.
Multivariable Control Theory.
(3)
Hermite, Smith and Smith-McMillan canonic forms for polynomial and rational matrices. Coprime matrix-fraction representations for rational matrices. Bezout identity. Poles and zeros for multivariable systems. Matrix-fraction approach to feedback system design. Optimal linear-quadratic-Gaussian (LQG) control. Multivariable Nyquist stability criteria.
Prerequisite: 500
547.
Neural Networks.
(3)
(Also offered as CS 547)
A study of biological and artificial neuron models, basic neural architectures and parallel and distributed processing.
548 / 448.
Fuzzy Logic with Applications.
(3)
(Also offered as CE 548)
Theory of fuzzy sets; foundations of fuzzy logic. Fuzzy logic is shown to contain evidence, possibility and probability logics; course emphasizes engineering applications; control, pattern recognition, damage assessment, decisions; hardware/software demonstrations
549.
Information Theory and Coding.
(3)
An introduction to information theory. Fundamental concepts such as entropy, mutual information, and the asymptotic equipartition property are introduced. Additional topics include data compression, communication over noisy channels, algorithmic information theory, and applications.
Prerequisite: 340 or equivalent
550.
Social and Ethical Issues in Nanotechnology.
(1-3 [3])
Mills, Fledderman
(Also offered as CHNE, NSMS 550)
In this course, students will examine issues arising from this emerging technology, including those of privacy, health and safety, the environment, public perception and human enhancement.
551.
Problems.
(1-6 to a maximum of 9 ?)
553L.
Experimental Techniques in Plasma Science.
(3)
(Also offered as CHNE 553L)
Theory and practice of plasma generation and diagnostics, coordinated lectures and experiments, emphasis on simple methods of plasma production and selection of appropriate diagnostic techniques, applications to plasma processing and fusion.
Prerequisite: 534
554.
Advanced Optics II.
(3)
(Also offered as PHYC 554)
Diffractions theory, coherence theory, coherent objects, and incoherent imaging, and polarization.
555.
Foundations of Engineering Electromagnetics.
(3)
Mathematical foundations for engineering electromagnetics: linear analysis and method of moments, complex analysis and Kramers-Kronig relations, Green’s functions, spectral representation method and electromagnetic sources.
556 / 456.
Entrepreneurial Engineering.
(3)
(Also offered as ME 556)
Review and application of necessary elements for successfully launching technical businesses; focuses upon technology, manufacturing, management, marketing, legal and financial aspects. Students work in groups developing elements of new businesses and producing business plans.
557.
Pulsed Power and Charged Particle Acceleration.
(3)
Principles of pulsed power circuits, components, systems and their relationship to charged particle acceleration and transport. Energy storage, voltage multiplication, pulse shaping, insulation and breakdown and switching. Single particle dynamics and accelerator configurations.
558.
Charged Particle Beams and High Power Microwaves. .
(3)
(Also offered as CHNE 546)
Overview of physics of particle beams and applications at high-current and high-energy. Topics include review of collective physics, beam emittance, space-charge forces, transport at high power levels, and application to high power microwave generation.
Prerequisite: 557 and CHNE 546
559.
Internship in Optical Science and Engineering.
(3)
(Also offered as PHYC 559)
Students do research and/or development work at a participating industry or government laboratory in any area of optical science and engineering.
560 / 460.
Introduction to Microwave Engineering.
(3)
This lecture/laboratory course provides essential fundamentals for rf, wireless and microwave engineering. Topics include: wave propagation in cables, waveguides and free space; impedance matching, standing wave ratios, Z- and S- parameters.
561.
Engineering Electromagnetics .
(3)
Maxwell’s equations, electromagnetic interaction with materials, the wave equation, plane wave propagation, wave reflection and transmission, vector potentials and radiation equations, electromagnetic field theorems, wave propagation in anisotropic media and metamaterials, period structures, dielectric slab waveguides.
Prerequisite: 555
563.
Computational Methods for Electromagnetics.
(3)
Computational techniques for partial differential and integral equations: finite-difference, finite-element, method of moments. Applications include transmission lines, resonators, waveguides, integrated circuits, solid-state device modeling, electromagnetic scattering and antennas.
Prerequisite: 561
564.
Guided Wave Optics.
(3)
Optical propagation in free space, colored dielectrics, metals, semiconductors, crystals, graded index media. Radiation and guided modes in complex structures. Input and output coupling, cross-coupling mode conversion. Directional couplers, modulators, sources and detectors.
565.
Optical Communication Components and Subsystems.
(3)
Optical waveguides, optical fiber attenuation and dispersion, power launching and coupling of light, mechanical and fiber lifetime issues, photoreceivers, digital on-off keying, modulation methods, SNR and BER, QAM and M-QAM, modulation methods, SNR, and BER, intersymbol interference (impact on SNR), clock and data recovery issues, point-to-point digital links, optical amplifiers theory and design (SOA, EDFA, and SRA), simple WDM system concepts, WDM components.
566.
Advanced Optical Subsystems and Networks.
(3)
External modulators WDM system design, other multiple access techniques design issues, analog transmission systems nonlinear processes in optical fibers and their impact on system performance, optical networks, photonic packet switching, coherent lightwave systems, basic principles for homodyne and heterodyne detection, noise reduction, relevant digital modulation formats: PSK, ASK, FSK, DPSK. Practical implementation, performance of synchronous and asynchronous heterodyne systems, phase noise, polarization mismatch.
Prerequisite: 565
569 / 469.
Antennas for Wireless Communications Systems.
(3)
Aspects of antenna theory and design; radiation from dipoles, loops, apertures, microstrip antennas and antenna arrays.
570.
Optoelectronic Semiconductor Materials and Devices.
(3)
Theory and operation of optoelectronic semiconductor devices; semiconductor alloys, epitaxial growth, relevant semiconductor physics (recombination processes, heterojunctions, noise, impact ionization), analysis of the theory and practice of important OE semiconductor devices (LEDs, Lasers, Photodetectors, Solar Cells).
Prerequisite: 471 or 572
572.
Semiconductor Physics.
(3)
Sigmon
(Also offered as NSMS 572)
Crystal properties, symmetry and imperfections. Energy bands, electron dynamics, effective mass tensor, concept and properties of holes. Equilibrium distributions, density of states, Fermi energy and transport properties including Boltzmann’s equation. Continuity equation, diffusion and drift of carriers.
Prerequisite: 471
574L / 474L.
Microelectronics Processing.
(3)
Fledderman, Hersee
(Also offered as NSMS 574L)
Materials science of semiconductors, microelectronics technologies, device/circuit fabrication, parasitics and packaging. Lab project features small group design/fabrication/testing of MOS circuits.
575.
Junction Devices.
(3)
Advanced junction devices including VLSI bipolar transistors, Si-Ge and III-V HBTs, high-level injection, high-frequency devices.
Prerequisite: 471 or 572
576.
Modern VLSI Devices.
(3)
Review of the evolution of VLSI technology and basic device physics. Detailed analysis of MOSFET devices, CMOS device design including device scaling concepts.
Prerequisite: 471 or 572
577.
Fundamentals of Semiconductor LEDs and Lasers.
(3)
Carrier generation and recombination, photon generation and loss in laser cavities, density of optical modes and blackbody radiation, radiative and non-radiative processes, optical gain, spontaneous and stimulated emission, Fermi’s golden rule, gain and current relations, characterizing real diode lasers, dynamic effects, rate equation; small signal and large signal analysis, radiative intensity noise and linewidth.
Prerequisite: 572
578.
Advanced Semiconductor Lasers.
(3)
Scattering matrix theory, S and T matrices, gratings, DBR and DFB lasers, perturbation and coupled-mode theory, photonic integrated circuits, tunable lasers, directional couplers.
Prerequisite: 577
580.
Advanced Plasma Physics.
(3)
(Also offered as PHYC 580)
Prerequisite: 534 or PHYC 534
581.
Colloidal Nanocrystals for Biomedical Applications.
(3)
(Also offered as BIOM, NSMS 581)
Intended for students planning careers combining engineering, materials science, and biomedical sciences. Covers synthesis, nanocrystals characterization, biofunctionalization, biomedical nanosensors, FRET-based nanosensing, molecular-level sensing/imaging, and applications in cell biology, cancer diagnostics and therapy, neuroscience, and drug delivery.
585.
Modern Manufacturing Methods.
(3)
(Also offered as ME 585)
Study of business of manufacturing, emphasizing modern approaches. Topics include: U.S. manufacturing dilemma; JIT, kanban, pull manufacturing, quality; modeling; design for production; manufacturing economics; management issues; DIM; case studies.
586 / 486.
Design for Manufacturability.
(3)
(Also offered as ME 586)
Introduction to methods of design for manufacturability (DFM). Emphasis is on teamwork and designing your customers needs. This is achieved through statistical methods and computer based systems.
590.
Graduate Seminar.
(1 to a maximum of 2 ?)
Offered on a CR/NC basis only.
591.
Integrating Nanotechnology with Cell Biology and Neuroscience Seminar.
(1, no limit ?)
Graduate seminar on Integrating Nanotechnology with Cell Biology and Neuroscience. Grades based on active participation, including oral presentation.
594.
Complex Systems Theory.
(3)
Advanced topics in complex systems including but not limited to biological systems social and technological networks, and complex dynamics.
Prerequisite: graduate standing
595 / 495.
Special Topics.
(1-4 to a maximum of 15, 1-4 to a maximum of 9 ?)
599.
Master?s Thesis.
(1-6, no limit ?)
Offered on a CR/NC basis only.
609.
Advanced Parallel Algorithms.
(3)
(Also offered as CS 609)
Design and analysis of advanced parallel algorithms, parallel complexity theory, ideal and realistic models of parallel computation, and experimental parallel algorithmics; emphasis on combinatorial problems.
Prerequisite: 509 or CS 509
620.
Topics in Interdisciplinary Biological and Biomedical Sciences.
(3, unlimited ?)
(Also offered as ANTH 620, BIOL 520, CS 520, STAT 520)
Varying interdisciplinary topics taught by collaborative scientists from UNM, SFI, and LANL.
637.
Topics in Algorithms.
(3 to a maximum of 9 ?)
Advanced topics including advanced computer architecture, networks, distributed computing, large-scale resource management, high-performance computing and grid-based computing.
Prerequisite: 537
638.
Topics in Architecture and Systems.
(3 to a maximum of 9 ?)
Advanced topics including advanced computer architecture, networks, distributed computing, large-scale resource management, high-performance computing and grid-based computing.
Prerequisite: 538
642.
Detection and Estimation Theory.
(3)
Hypothesis testing; Karhunen-Loeve representation; optimal detection of discrete- and continuous-time signals; ML, MMSE, and MAP estimation; sufficient statistics, estimation error bounds; Wiener and Kalman-Bucy filtering; detection/receivers for multiuser and multipath fading channels.
Prerequisite: 541
649.
Topics in Control Systems.
(3 to a maximum of 9 ?)
Prerequisite: 546
651.
Problems.
(1-6 to a maximum of 9 ?)
661.
Topics in Electromagnetics.
(3)
Topics include advanced antenna theory, electromagnetic scattering and propagation, electromagnetic compatibility, low temperature plasma science, advanced plasma physics, and other subjects in applied electromagnetics.
Prerequisite: 561
699.
Dissertation.
(3-12, no limit ?)
Offered on a CR/NC basis only.
511.
Analysis Methods in Functional Magnetic Resonance Imaging.
(3)
This course will be an introduction to signal and image processing methods for functional magnetic resonance imaging (fMRI) of the brain.
