Electronics

The lectures include basic theory of signals, circuits and systems, the theory of continuous time filter design. Taking Butterworth filter design as an example, the students learn the design methods for Butterworth passive and active filter design. The designed circuits are simulated by SPICE program. For digital filter design, the students must know how to design FIR and IIR filters. The designed filters are used to remove the noise of the polluted signals, the spectrum and performance are compared before and after filtering.

The course covers languages, tools, and techniques for developing interactive and dynamic web pages. Topics include page styling, design, and layout using XHTML and CSS, client and server side scripting with PHP and JavaScript, web security, and interacting with data sources such as XML files. Primary programming experience is required, and the students should be familiar with the use of a computer.

This course is a required course designed for Engineering Master of Computer Science in TIEI. This course will systematically describe data file processing, the basic knowledge of probability and statistic, parameter estimation, hypothesis testing, variance analysis, regression analysis and so on. The purpose of this course is to equip students with the basic knowledge of data analysis, teach students how to apply scientific statistical theory and methods to understand objective things, enhance student’s ability to analyze and solve practical problems and lay the foundation for other courses.

Numerical Tools is an introductory course in numerical methods, MATLAB, and technical computing. It emphasizes the informed use of mathematical software. Topics include matrix computation, interpolation and zero finding, differential equations, random numbers, and Fourier analysis.

The course covers the following topics:

Ÿ  One-Parameter Processes, Usually Functions of Time

Ÿ  Markov Processes

Ÿ  Stochastic Calculus, Diffusions, and Spectra

Ÿ  Ergodic Theory

  Large Deviations Theory

The course takes a unified view of optimization and covers the main areas of application and the main optimization algorithms. It covers the following topics:

Ÿ  Linear optimization

Ÿ  Robust optimization

Ÿ  Network flows

Ÿ  Discrete optimization

Ÿ  Dynamic optimization

  Nonlinear optimization

The course introduces various structures of micro-computer systems, techniques for designing a computing system and methods for analyzing its performance, instruction set of the processor, interface between processor and memory, I/O devices. The course provides preliminary knowledge for developing an applicable computer or embedded system.

Ÿ  Information Quantity: Entropy, Joint Entropy, Conditional Entropy, Mutual Information, Differential Entropy

Ÿ  Data Compression: Kraft Inequality, Optimal Codes and Bounds on Code Length, Huffman Codes, Lossy Quantization, Rate Distortion Function

Channel Capacity: Channel, Symmetric Channels, Channel Capacity, Channel Coding Theorem

The course will have an extensive coverage of media compression, synthesis and recognition, media communications and networking, and standards for audio-visual communications over wired and wireless networks.

The course covers the following topics:

Ÿ  Design of IIR filters from analog filters       

Ÿ  Design of linear phase FIR filters

Ÿ  Nonlinear effects of finite word length implementations of digital   filters; limit cycles and overflow oscillations   

Ÿ  Statistical analysis of roundoff noise in digital filters        

  Wave digital filters; state-space structures for digital filters

The course covers the following topics:

Ÿ  Fourier series, the Fourier transform of continuous and discrete signals and its properties.

Ÿ  The Dirac delta, distributions, and generalized transforms.

Ÿ  Convolutions and correlations and applications, probability distributions, sampling theory, filters, and analysis of linear systems.

Ÿ  The Discrete Fourier transform and the FFT algorithm.

Ÿ  Multidimensional Fourier transform and use in imaging.

  Further applications to optics, crystallography.

Ÿ  Advanced Filtering Theory: Wiener filtering; Adaptive filtering (including Kalman filtering, LMS filtering, RLS filtering etc.)

Ÿ  Advanced Spectral Analysis Theory: Eigenvalue Analysis and Principal Component Analysis (including MUSIC and ESPRIT spectral analyzer, etc.), Modern spectral analysis.

  Blind Signal Processing Theory: Blind deconvolution, Blind Signal Separation, Blind Equalisation, etc.

  The lectures include basic theory of signals, circuits and systems, the theory of continuous time filter design. Taking Butterworth filter design as an example, the students learn the design methods for Butterworth passive and active filter design. The designed circuits are simulated by SPICE program. For digital filter design, the students must know how to design FIR and IIR filters. The designed filters are used to remove the noise of the polluted signals, the spectrum and performance are compared before and after filtering..

"Digital Processing and Computer” is an important professional foundation course for information and computer science. The function representations of signal and system analysis are taught. Master the time domain of the continuous time system and the discrete time system and frequency domain analysis, S domain, F domain analysis of continuous time system and Z domain analysis of discrete time system, state equation and state variable analysis method and so on. Through the computer practice and system design, the students master the basic method of using the computer to carry out the signal and system analysis, and it trains the students' experimental skills and scientific analysis methods for the signals and systems.

This course covers various basic topics in wireless communications for voice, data, and multimedia. It begins with an overview of current wireless systems and standards, followed by a characterization of the wireless channel, including path loss, shadowing, and the flat vs. frequency-selective properties of multipath fading. It then examines the fundamental capacity limits of wireless channels and the characteristics of the capacity-achieving transmission strategies. This part is followed by practical digital modulation techniques and their performance under wireless channel impairments, including diversity techniques to compensate for flat-fading, multicarrier modulation to combat frequency-selective fading, and an introduction to multi-antenna communications. The course concludes with a discussion of various practical multiple access schemes in wireless cellular systems.

Much of the class will focus on network algorithms and their performance. Students are expected to have a strong mathematical background and an understanding of probability theory. Topics discussed will include layered network architecture, Link Layer protocols, high-speed packet switching, queuing theory, Local Area Networks, and Wide Area Networking issues including routing and flow control.

It includes interference and propagation link analysis, earth station and satellite technology, antenna, RF/microwave transceiver and architecture, modulation and coding, multiple access techniques, as well as advanced technologies such as multibeam, inter satellite link, and regenerative satellite transponders.

Ÿ  Image formation: camera model, camera calibration, radiometry, color, shading

Ÿ  Early vision: Stereo, structure from motion, illumination, reflectance,

Ÿ  Mid-level vision: feature detection and extraction

  High-level vision: object detection, object recognition, visual tracking

This course will include some fundamental technologies for digital image, image processing in spatial domain/frequency domain, image restoration, linear image filtering and correlation, noise reduction and restoration, feature extraction, morphological image processing, and image segmentation.

The course covers the following topics:

The propagation, reflection, and transmission of plane waves, and the analysis and design of multilayer films.

Waveguides, transmission lines, impedance matching, and S-parameters.

Linear and aperture antennas, scalar and vector diffraction theory, antenna array design, and coupled antennas.

To study physical phenomena which governs electrical behavior of semiconductors.

Much of the class will focus on network algorithms and their performance. One of the goal of this course is to increase the students’ ability to define requirements when defining a link level procedure for data communication.

VLSI design flow, FPGA structures and principles

Design FSM, Verilog

Digital system design based on FPGA using Verilog

This class deals with the modeling and analysis of queuing systems, with applications in communications, manufacturing, computers, call centers, service industries and transportation. Topics include birth-death processes and simple Markovian queues, networks of queues and product form networks, single and multi-server queues, multi-class queuing networks, fluid models, adversarial queuing networks, heavy-traffic theory and diffusion approximations. The course will also cover state of the art results which lead to research opportunities.

This is a graduate level specialization course
designed to cover the state-of-the-art techniques in the field of embedded
intelligent vision guided autonomous vehicles, early vision of ROI
localization, Canny and LoG edge detection and segmentation, Hough Transforms
and moments-based feature extraction, Laser Imaging Radar, Ultrasonic range
finder and their integration with Stereo Vision Sensors. Also included are
vision guided path extraction, driving obstacle/hazardous objects detection,
vehicle nonlinear control modelling, PID, Kalman control with integration of
intelligent controller design, OpenCV and OpenGL tool for implementations and
GPU technology. Also required are four hands-on labs with embedded GPU
platform.

This is a course on the fundamentals of data communication networks, their architecture, principles of operations, and performance analyses.

A digital communication system is one that transmits a source (voice, video, data, etc.) from one point to another, by first converting it into a stream of bits, and then into symbols that can be transmitted over channels (cable, wireless, storage, etc.). The use of the digital bit-stream as the interface between the source and the channel is universal regardless of what kind of source and channel are involved. Digital communication principle, with "bit" as the most important concept of the information age, and applications in computer science, Internet, wireless, etc., is one of the most successful stories of applying mathematics to engineering designs.

The course gives an overview of the designs of digital communications systems. We explain the mathematical foundation of decomposing the systems into separately designed source codes and channel codes. We introduce the principles and some commonly used algorithms in each component, to convert continuous time waveforms into bits, and vice versa. We give a comprehensive introduction to the basics of information theory, a rather thorough treatment of Fourier transforms and the sampling theorem, and an overview of the use of vector spaces in signal processing.

Since machine learning can only be understood through practice, by using the algorithms, the course is accompanied with assignments during which students test a variety of machine learning algorithm with real world data. The course uses the MLDEMOS TOOLBOX that entails a large variety of machine learning algorithms.

Binary and multi-class classifiers: LDA, GMM with Bayes, SVM, Boosting

Pattern recognition and clustering

Non-linear Regression

Markov-Based Techniques for Time Series Analysis

Topics covered in this course include modelling of speech signal generation, pre-processing of speech signal, such as de-noising and enhancing, speech analyzing in time domain, speech analyzing in frequency domain, LPC, Pitch Estimation and Formant Estimation,HMM and Vector Quantization, Speech Coding and Speech Synthesis and Recognition.

This course will introduce the fundamental principles of optical communication systems. The main topics include optics, fiber, laser, optical modulator, modulation formats, polarization, and photodetector.

In the field of electronic and communication engineering, professional developers should master a variety of programming development tools to achieve the simulation and development in the real application. The content of this course is mainly divided into two categories: one is generic general high language for design and simulation, such as MATLAB, Python, etc., the other is for application implementation and development software, such as C / C ++. After students learn the basic programming method and knowledge, they need complete the software development of some basic function modules, which are selected according to their own scientific research direction. In this process, students will learn the high programming language, master some programming specifications, and improve the programming and debugging skills. Finally this project will lay a solid foundation for the future development of the actual application system.

According to the requirements of the project, the teacher will give the research contents and basic direction of this project. Under the guidance of the instructor, 

the students will complete a series of design and development work,

such as how to analysis a real project, 

how to collect and collate the reference document, 

and how to design and simulate a basic algorithm or module  .

 According to the training objectives, the tutor will choose a project related to the applications, the students will need complete this basic research or engineering development project (the workload not less than 2 months) .

Based on the previous three semester project, the students will finish a comprehensive summary of their work in the postgraduate stage, and writing internship reports or thesis to demonstrate their research results. This term project mainly trains the students' ability of generalization, academic writing and problem analysis.

The course is a required course designed for Engineering Master of Computer Science in TIEI. It will systematically describe how to carry out programming under Linux environment. It not only introduces the main components of Linux system, but also explains in detail the Linux Kernel, the guidance system, file system, etc. At the same time, it combines some experimental projects to cultivate students’ practical application ability and innovation ability. Through learning of this course, students will have a preliminary understanding of Linux programming, and they are supposed to be more effective and steady to develop programs.

Modern analog circuit are electronic components that exploit the electronic properties of mos transistor. Analog circuit can be used as the building blocks of complex SoC system, which play an critical role in modern information age. This course provides a basis for understanding theory, analysis, simulation, and design of semiconductor devices.