Review of the frequency concept; analysis of circuits as linear systems, frequency response of circuits; introduction to communication systems, analog/digital modulation and demodulation; analog amplitude, frequency and phase modulation; digital amplitude shift keying, frequency shift keying and phase shift keying; review of bilateral and unilateral Laplace transform; introduction to z-transform; introduction to analog and digital control systems, first and second order systems, stability of closed-loop systems; root-locus method; frequency-domain methods and bode plots.
Introduction to semiconductors and semiconductor device physics. Diode, bipolar junction transistor, and MOS field effect transistor circuit models for design and analysis of electronic circuits. Analysis and design of single and multistage amplifiers. Amplifier operating point design. High frequency and low frequency response of single and multistage amplifiers. Introduction to integrated-circuit amplifiers.
Review of Maxwell's equations; conservation laws; electromagnetic waves; propagation of electromagnetic waves in conductors and dielectrics; transmission lines; waveguides; potentials and fields; radiation theory; electrodynamics and special theory of relativity.
An introduction to the design of embedded systems with an emphasis on understanding the microcomputer fundamentals by relating hardware, software and the physical applications. Topics covered include architecture and operation of a typical microprocessor, assembly language programming, serial and parallel input/output, memory (RAM and ROM), interrupts, concurrency management, and real-time constraints.
Fundamental concepts of sensors, driving/readout electronics; rational design of sensors, state-of-the-art commercial sensing, remote sensing, Internet of Things; Strain, piezoelectric, pressure, temperature, GPS, chemical, biological, resistive, capacitive sensors, photodetectors, accelerometers, gyroscopes; optical, magnetic sensors, RF sensors, power electronics, self-powered sensors; Sensor networks based on WiFi, 4G, Bluetooth; Human/Animal sensory systems; Feedback control systems; Microfabrication of sensors
Discrete and continuous random variables and processes, functions of random variables, independence of random variables. Central Limit Theorem. Discrete-time random processes, continuous-time random processes, stationary random processes, ergodicity, auto and cross correlation functions, power spectral density, spectral estimation, white noise processes, Markov chains.
Linear Algebra Review, Normal Matrices, Quadratic Forms and Semidefinite Matrices, Inner Product and Norm Spaces, State Space Descriptions for Continuous and Discrete Time Systems, Controllability, Observability, Stability, Realization Theory.
Study of computational models of visual perception and their implementation in computer systems. Topics include: image formation; edge, corner and boundary extraction, segmentation, matching, pattern recognition and classification techniques; 3-D Vision: projection geometry, camera calibration, shape from stereo/silhouette/shading, model-based 3D object recognition; color texture, radiometry and BDRF; motion analysis.
Entropy, Relative Entropy and Mutual Information; Asymptotic Equipartition Theory; Entropy Rates of a Stochastic Process; Data Compression; Kolmogorov Complexity; Channel Capacity; Differential Entropy; The Gaussian Channel; Maximum Entropy and Spectral Estimation; Rate Distortion Theory, Network Information Theory.
Probability theory, stochastic processes, characterization of digital communication signals and systems, digital modulation schemes, optimum receivers for additive white gaussian noise (AWGN) channels, signal design for band-limited channels, inter-symbol interference (ISI), optimum reception for channels with ISI and AWGN, linear equalization, adaptive equalization, entropy and source coding, channel capacity and coding.
Principles of computer networks and network protocols; Internet protocol stack with emphasis on application, transport, network and link layers; network edge and network core; client/server and peer-to-peer models; routing algorithms; reliable data transfer; flow and congestion control; protocol design and analysis; network performance metrics; software-defined networks; network programming and distributed applications.
Introduction to mathematical formulations and computational techniques for the modeling and simulation of engineering and other kinds of systems, including electronic, mechanical, biological, biochemical, virtual, abstract and multi-domain dynamical systems. Applications from various engineering disciplines and the sciences. Matrix formulation of equations for linear problems. Formulation of equations for nonlinear problems & linearization. Numerical solution of linear algebraic equations. Gaussian elimination, computations with sparse & structured matrices. Floating point number representation & arithmetic. Numerical conditioning, ill-conditioned problems. Numerical solution of nonlinear algebraic equations. Fixed point iteration & Newton’s method in one dimension. Newton’s method for system of coupled nonlinear algebraic equations. Improving convergence of Newton’s method. Numerical solution of ordinary differential equations. Forward & backward Euler, trapezoidal rule. Multistep methods, accuracy & stability. Implicit vs explicit techniques, region of stability, stiff problems.
Review of electromagnetism; electromagnetic nature of light, radiation, geometrical optics, Gaussian beams, transformation of Gaussian beams; electromagnetic modes of an optical resonator, interaction of light with matter, classical theory of absorption and dispersion, broadening processes, Rayleigh scattering, quantum theory of spontaneous and stimulated emission, optical amplification, theory of laser oscillation, examples of laser systems, Q switching and mode locking of lasers.
Design, simulation, and optimization of integrated photonics structures, the notion of fabless silicon photonics, metal and dielectric waveguides, planar waveguide modes, coupled mode theory, integrated passive couplers and splitters, Mach-Zehnder Interferometers, ring and disk resonators, adiabatic couplers, Bragg gratings, grating and edge couplers, photonic crystal waveguides and structures, principles of integrated modulator and detector operation, fabrication-dependent design considerations, use of transfer matrix, eigenmode expansion, and finite difference time-domain simulation techniques throughout the semester, design oriented and simulation based assignments and term project.
Introduction to device physics fundamentals of emerging energy technologies, the fundamentals of the latest innovations and research in different energy devices, a wide range of energy devices, such as solar cells, batteries, hydropower, wind power, thermoelectric, and biomass devices the physical and engineering principles underlying each technology including their economical advantages and drawbacks, how these technologies can be integrated to grid what are smart grid functions, grid energy storage, electric vehicles, etc.
A broad introduction to machine learning covering regression, classification, clustering, and dimensionality reduction methods; supervised and unsupervised models; linear and nonlinear models; parametric and nonparametric models; combinations of multiple models; comparisons of multiple models and model selection.
A capstone design course where students apply engineering and science knowledge in an electrical-electronics engineering design project. Development, design, implementation and management of a project in teams under realistic constraints and conditions. Emphasis on communication, teamwork and presentation skills..
A capstone design project on an industrially relevant problem. Students work on teams in consultation with various faculty and industrial members.
Discrete and continuous random variables and processes, functions of random variables, independence of random variables. Central Limit Theorem. Discrete-time random processes, continuous-time random processes, stationary random processes, ergodicity, auto and cross correlation functions, power spectral density; spectral estimation, white noise processes, Markov chains.
Linear Algebra Review, Normal Matrices, Quadratic Forms and Semidefinite Matrices, Inner Product and Norm Spaces, State Space Descriptions for Continuous and Discrete Time Systems, Controllability, Observability, Stability, Realization Theory.
Study of computational models of visual perception and their implementation in computer systems. Topics include: image formation; edge, corner and boundary extraction, segmentation, matching, pattern recognition and classification techniques; 3-D Vision: projection geometry, camera calibration, shape from stereo/silhouette/shading, model-based 3D object recognition; color texture, radiometry and BDRF; motion analysis.
Entropy, Relative Entropy and Mutual Information; Asymptotic Equipartition Theory; Entropy Rates of a Stochastic Process; Data Compression; Kolmogorov Complexity; Channel Capacity; Differential Entropy; The Gaussian Channel; Maximum Entropy and Spectral Estimation; Rate Distortion Theory, Network Information Theory.
Characterization of communication signals & systems, digital modulation schemes, optimum reception for the additive white Gaussian noise (AWGN) channel, signal design for band-limited channels, Nyquist criterion, intersymbol interference (ISI), optimum reception for channels with ISI and AWGN, linear equalization, decision feedback equalization, adaptive equalization, channel capacity & coding, linear block codes, convolutional codes, multichannel and multicarrier systems, spread spectrum signals for digital communications, multiuser communications. Design oriented exercises using computer aids.
Introduction to mathematical formulations and computational techniques for the modeling and simulation of engineering and other kinds of systems, including electronic, mechanical, biological, biochemical, virtual, abstract and multi-domain dynamical systems. Applications from various engineering disciplines and the sciences. Matrix formulation of equations for linear problems. Formulation of equations for nonlinear problems & linearization. Numerical solution of linear algebraic equations. Gaussian elimination, computations with sparse & structured matrices. Floating point number representation & arithmetic. Numerical conditioning, ill-conditioned problems. Numerical solution of nonlinear algebraic equations. Fixed point iteration & Newton’s method in one dimension. Newton’s method for system of coupled nonlinear algebraic equations. Improving convergence of Newton’s method. Numerical solution of ordinary differential equations. Forward & backward Euler, trapezoidal rule. Multistep methods, accuracy & stability. Implicit vs explicit techniques, region of stability, stiff problems.