Various polytechnics offer diploma in various disciplines of engineering. Industry Sponsored Topics include Markov decision processes (MDP), Pontryagin’s maximum principle, linear quadratic regulation (LQR), deterministic planning, value and policy iteration, and policy gradient methods. 15 and 25 with grades of C– or better. ECE 141B builds upon the solid C++ foundation of ECE 141A. in Photonics/Applied Optics (2). This is a combined introductory graduate/upper-level undergraduate course that focuses on examining modern techniques for manipulating cellular behavior and the application of these techniques to problems in the biomedical and biotechnological arenas. Students will work weekly in the lab learning cell culture techniques, soft lithography, microscopy, and classical in vitro assays measuring cell behavior.
Our focus will be on foundational signal processing concepts that can be applied in a variety of biological applications.
Prerequisites: ECE 258A; graduate standing. Integrated Circuits and Systems IV (4). (Course materials and/or program fees may apply.) Prerequisites: consent of instructor. and formulating convex problems, duality, and applications in a variety Passive microwave elements.
Prerequisites: graduate standing.
Digital Signal Processing I (4).
03:00pm to 04:15pm. ECE 256. Recommended preparation: ECE 155.
ECE 265A. Students will apply their prior knowledge in C (from ECE15) to program microcontrollers and will engage in data analysis using the Python programming language.
Familiarity with basic microwave design and communication system architecture is assumed. Probability and Statistics for Data Science (4). Introduction to Intelligent Systems: Robotics and Machine Intelligence (4). Statistical pattern classifiers. Evolutionary biology (e.g., the study of the tree of life) uses computational methods from statistics and machine learning. Students who have taken ECE 259BN may not receive credit for ECE 259B.
Working in small teams, students will develop 1:8 scale autonomous cars that must perform on a simulated city track.
ECE 294. Design and performance analysis of digital modulation techniques, including probability of error results for PSK, DPSK, and FSK. and Random Processes for Engineers (4).
Recommended preparation: ECE 230A and ECE 230C or equivalent. ECE 230C. ECE 236C. Covers the same subjects that actual power system operators’ certification course covers. B.E. Microwave and RF system design communications. ECE 229. Communications Systems Laboratory II (4). This course provides an introduction to statistical learning and assumes familiarity with key statistical methods. Prerequisites: ECE 65 and PHYS 2D or PHYS 4D and 4E. Prerequisites: ECE 272A; graduate standing.
Prerequisites: admission to the ECE departmental honors program.
Antenna impedance, beam pattern, gain, and polarization. Recommended preparation: ECE 143 (for Python) or equivalent proficiency in Matlab programming. Nonideal effects and their mitigation in high-performance operational amplifiers. (Electrical Engineering) + M.Tech. Student design teams prepare a research proposal and participate in a weekly laboratory. Business Knowledge: The use of business model analysis and lean experimentation methods to develop and test a set of hypotheses that capture how the new product/service will create value, including business model design, pricing, sales and marketing, operating model and profit formula. Launch Lab therefore focuses on the practical application of these skills to team projects, supplemented by content in three areas: i) seminars on advanced methods and techniques, ii) workshops that demonstrate how to put these skills and tools into practice, and iii) guest speakers who share their experience in the areas of design, technology and business.
Analog-to-digital and digital-to-analog conversion. Optical fibers, waveguides, laser communication Prerequisites: CSE 11 or CSE 8B or ECE 15. Bayesian inference and risk. Linear least Squares (batch, recursive, total, sparse, pseudoinverse, QR, SVD); Statistical figures of merit (bias, consistency, Cramer-Rao lower-bound, efficiency); Maximum likelihood estimation (MLE); Sufficient statistics; Algorithms for computing the MLE including the Expectation Maximation (EM) algorithm. of all of the breadth courses and one depth course. Modern Communication Networks (4).
The hardware platforms include CPU-CPU and CPU-GPU architectures. 03:00pm to 05:45pm. Statics and dynamics of fluids. ECE 264D. characteristic functions, transformation of random variables, central limit
Power Amplifiers for Wireless Communications (4). Course provides exposure to problem definition, problem framing, qualitative and quantitative research methods, modeling, generation and co-design of creative solutions, engineering design trade-offs, and documentation/communication skills. Tuesday, Thursday
The linear least squares problem, including constrained and unconstrained quadratic optimization and the relationship to the geometry of linear transformations. Diffusion equations, linear and nonlinear estimation and detection, random fields, optimization of stochastic dynamic systems, applications of stochastic optimization to problems. Case studies of current pharmaceutical products. tomography, nuclear medicine imaging, nuclear magnetic resonance imaging, Sparse array design and processing techniques. Gu-Yeon Wei Design of instrumentation amplifiers, sensors, and electrical stimulation interfaces.
Prerequisites: none. The course will continue to explore best practices in software development, debugging, and testing. 212AN; graduate standing.
Prerequisites: ECE 107 with a grade of C– or better.
(S/U grades only.) Students that have taken 255BN cannot take 255B for credit. Down-conversion and up-conversion techniques. Topics vary based upon current research and have included nonparametric Bayesian models; sampling methods for inference in graphical models; Markov Chain Monte Carlo (MCMC) methods.
Experiments in the modulation and demodulation of baseband and passband signals. Students will research, design, and develop an IOT device to serve an emerging market. This course approaches a number of problems without the prejudice of trying to apply a particular method of solution. Forgot password?Submit your email address and we'll send you a link to reset your password.
Network/Graph Algorithms and Analysis (4). for more information.
Prerequisites: graduate standing. Monday ECE 269. The combination of statistics and algorithms produces statistical learning methods that automate the analysis of complex data. Consent of instructor is required.
Semiconductor crystal structure, energy bands, doping, carrier statistics, drift and diffusion, p-n junctions, metal-semiconductor junctions. Building on a solid foundation of electrical and computer engineer skills, this course strives to broaden student skills in software, full-stack engineering, and concrete understanding of methods related to the realistic development of a commercial product.
discovery, architectural principles.
Students who have already completed ECE 236C and/or D should not enroll in this course. Computer simulation of devices, scaling characteristics, high frequency performance, and circuit models. ECE 163. Subject matter will not be repeated, may be taken for credit more than once. Example course topics: Coded-modulation for bandwidth-efficient data transmission; advanced algebraic and combinatorial coding theory; space-time coding for wireless communications; constrained coding for digital recording. Introduction to pattern recognition and machine Prerequisites: graduate standing. Regression. In this course we will study the production, properties, and characterization of these molecules through the lens of food fermentation.
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