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This course provides an introduction to deep learning. Students taking this course will learn the theories, models, algorithms, implementation and recent progress of deep learning, and obtain empirical experience on training deep neural networks. The course starts with machine learning basics and some classical deep models (including convolutional neural network, deep belief net, and auto-encoder), followed by optimization techniques for training deep neural networks, implementation of large-scale deep learning, multi-task deep learning, transferred deep learning, recurrent neural networks, applications of deep learning to computer vision and speech recognition, and understanding why deep learning works. The students taking are expected to have some basic background knowledge on calculus, linear algebra, probability, statistics and random process as a prerequisite. (For ELEG UG (under 4-Year Undergraduate Curriculum) and ELEG RPG students as elective; Not for students who have taken ELEG5040.)
Review of semiconductor fundamentals: electron and hole, Fermi energy, generation and recombination, p-n junction, hopping, field-effect. Introduction to organic and polymeric semiconductors: morphology, molecular packing, conformation, electronic structures, optical and electrical properties. Application of organic/polymeric thin films: OLEDs, OTFTs, PLEDs, photodetectors and sensors. Fabrication methods for flexible electronics: sputtering, CVD, VPD, inkjet printing, screen printing, roll-to-roll printing, spraying coating, etc. Introduction to OLED/PLED based display technology: passive matrix OLED and active matrix OLED display techniques. Basic principles of photovoltaic devices: absorption, photo-electric conversion, conversion efficiency, loss mechanism, carrier collection, device characterization. Introduction to solar cell technology: monocrystalline solar cells; dye-sensitized solar cells; organic solar cells. (For ELEG RPG students, ELEG undergraduate major and minor students as elective course; Prerequisite: ELEG3301 or ELEG4301 or with the consent of the instructor.)
Theory of optical waveguides. Design techniques for optical waveguides. Numerical methods (FDTD, BPM etc) for optical waveguide simulations and their limitations. The use of commercial simulation and CAD layout tools to design optical waveguide devices such as directional couplers and splitters. Coupling techniques and losses in optical waveguides. Nonlinear effects and their applications. Optical modulators and optical interconnects. Recent trends and applications. (For ELEG RPG students, ELEG undergraduate major and minor students as elective course; Not for students who have taken ELEG4520.)
Review of physical properties of light. Optical sources and detectors. Interaction between light and biological materials. Introduction to cell and tissues, DNA and protein. Photo-absorption, emission and spectroscopy. Bio-imaging principles and techniques. Modeling of light-tissue interaction. Light-activated therapy. Micro-array technology. Laser tweezers. Emerging biophotonic technologies. (For ELEG RPG students, ELEG and BMEG undergraduate major and minor students as elective course; Not for students who have taken ELEG5521.)
Analog-digital ASIC design: technology trends, integration requirements, design skills and methodologies; Characteristics of modern IC technologies; Layout and Matching; Noise in electronic circuits; Coupling and isolation; Synthesis of basic cells: operational transconductance amplifiers, comparators, voltage and current references; Design of analog-digital integrated circuits at the building block and system level: continuous-time and sampled-data filters, Nyquist-rate A/D and D/A converters, oversampled A/D converters. (For ELEG major and minor undergraduate and ELEG RPg and TPg students as elective course; Not for students who have taken ELEG5201.)
