Signal Processing

PhD student John Jakabosky runs a proof-of-concept experiment on transmitter-in-the-loop optimization of advanced radar waveforms.

EECS researchers are building innovative signal processing techniques that exploit noise and interference for additional information or as cover for covert messages. They are developing static/adaptive filtering schemes that will better enable cooperative communication systems and networks. Remote sensing research of the polar ice caps has led to numerous developments in signal processing. New techniques and methods are being explored in computer vision, digital image processing, optical sensors, and other current EECS research.

Associated Disciplines

 

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Associated Programs

Associated Faculty

Professor
785-864-7326
Eaton Hall, room 3034

Primary Research Interests

  • Adaptive Signal Processing for Radar and Communications
  • Array Processing
  • Interference Cancellation
  • Waveform Diversity/Design for Physical Systems
  • Spectrum Engineering
Professor
785-864-8814
3026 Eaton Hall

Primary Research Interests

  • Optical/RF Measurement and Biosensors
  • Novel Photonic Devices
  • Optical Communication Systems
Associate Professor
785-864-5758
2052 Eaton Hall

Primary Research Interests

  • Radar Sounding
  • Radar Altimetry
  • Ground-Penetrating Radar
Professor
785-864-7370
2054 Eaton Hall

Primary Research Interests

  • Digital Communication Theory
  • Advanced Modulation Techniques
  • Channel Coding
  • Synchronization
  • Multiple-Input Multiple-Output Communications
Professor, Associate Chair for Undergraduate Studies
785-864-8823
2001C Eaton Hall

Primary Research Interests

  • Audio Signal Processing
  • Network Performance
Professor
785-864-8815
3048 Eaton Hall

Primary Research Interests

  • Software Radio Systems
  • Spread Spectrum and Military Communication Systems
  • Radio and Radar Signal Processing
  • DSP Applications in Acoustics and Radio Signals
  • Wireless Communication Systems
Associate Professor
785-864-8816
3016 Eaton Hall

Primary Research Interests

  • High Performance Scientific Computing Algorithms
  • Parallel Unstructured Mesh and Optimization Algorithms
  • Model Order Reduction
  • Computational Medicine
  • Image Processing
Associate Professor, Associate Chair for Graduate Studies
785-864-8803
2001F Eaton Hall

Primary Research Interests

  • Radar Remote Sensing of Vegetation
  • Propagation and Scattering in Random Media
  • Ground-Penetrating Radar
  • Radar Signal Processing
  • Applications of Information and Estimation Theory in Remote Sensing
Assistant Professor
785-864-8800
3012 Eaton Hall

Primary Research Interests

  • Computer vision
  • Image processing
  • Pattern recognition
  • Artificial intelligence
  • Robotics

Associated Facilities

  • Xilinx and Altera FPGA/SoC prototyping systems
  • Synplicity and Xilinx FPGA synthesis tools
  • ModelSim VHDL/Verilog simulation tools
  • Spectrum analyzers, oscilloscopes, and function generators
  • Prototype PC board fabrication tools
  • RF signal generators
  • Simulink
  • Computational cluster with over 1,000 processors connected to 37 TB of on-line storage

Program Objectives

  • Understand the fundamental principles involved with extracting signals from noise and interference.
  • Understand how to design appropriate static/adaptive filtering schemes according to the particular application, availability of prior information, and operational environment.
  • Understand the fundamental limitations imposed by physical systems that bound realizable performance.
  • Have the ability to effectively communicate complex, abstract concepts.

Core Coursework (MS)

EECS 744 Communications and Radar Digital Signal Processing
The application of DSP techniques to specialized communications and radar signal processing subsystems. Topics include A-D converters, specialized digital filters, software receiver systems, adaptive subsystems and timing. Prerequisite: An undergraduate course in DSP such as EECS 644. LEC.
Spring 2018
Type Time/Place and Instructor Credit Hours Class #
LEC Prescott, Glenn
MWF 11:00-11:50 AM LEA 3150 - LAWRENCE
3 62082
LEC Prescott, Glenn
MWF 11:00-11:50 AM KS-ST OLTH - EDWARDS
3 62850
EECS 844 Adaptive Signal Processing
This course presents the theory and application of adaptive signal processing. Topics include adaptive filtering, mathematics for advanced signal processing, cost function modeling and optimization, signal processing algorithms for optimum filtering, array processing, linear prediction, interference cancellation, power spectrum estimation, steepest descent, and iterative algorithms. Prerequisite: Background in fundamental signal processing (such as EECS 644.) Corequisite: EECS 861. LEC.

The class is not offered for the Spring 2018 semester.

EECS 861 Random Signals and Noise
Fundamental concepts in random variables, random process models, power spectral density. Application of random process models in the analysis and design of signal processing systems, communication systems and networks. Emphasis on signal detection, estimation, and analysis of queues. This course is a prerequisite for most of the graduate level courses in radar signal processing, communication systems and networks. Prerequisite: An undergraduate course in probability and statistics, and signal processing. LEC.

The class is not offered for the Spring 2018 semester.

EECS 965 Detection and Estimation Theory
Detection of signals in the presence of noise and estimation of signal parameters. Narrowband signals, multiple observations, signal detectability and sequential detection. Theoretical structure and performance of the receiver. Prerequisite: EECS 861. LEC.

The class is not offered for the Spring 2018 semester.

Elective Coursework (MS)

EECS 611 Electromagnetic Compatibility
A study of unwanted generation and reception of radio-frequency radiation from analog and digital electronic systems and how these emissions/receptions can be reduced. Topics covered include sources of radiation, grounding, shielding, crosstalk, electrostatic discharge, and practical design and layout schemes for reducing unwanted radiation and reception. Also covered are the major governmental electromagnetic compatibility (EMC) regulations and standards that apply to commercial electronic devices and systems. Prerequisite: EECS 220 and EECS 312. LEC.
Spring 2018
Type Time/Place and Instructor Credit Hours Class #
LEC Demarest, Kenneth
MWF 12:00-12:50 PM LEA 1131 - LAWRENCE
3 65744
EECS 622 Microwave and Radio Transmission Systems
Introduction to radio transmission systems. Topics include radio transmitter and receiver design, radiowave propagation phenomenology, antenna performance and basic design, and signal detection in the presence of noise. Students will design radio systems to meet specified performance measure. Prerequisite: Corequisite: EECS 420 and EECS 461. LEC.

The class is not offered for the Spring 2018 semester.

EECS 628 Fiber Optic Communication Systems
Description and analysis of the key components in optical communication systems. Topics covered include quantum sources, fiber cable propagation and dispersion characteristics, receiver characteristics, and system gain considerations. Prerequisite: EECS 220 and PHSX 313 or equivalent and upper-level EECS eligibility. LEC.
Spring 2018
Type Time/Place and Instructor Credit Hours Class #
LEC Hui, Rongqing
MWF 03:00-03:50 PM LEA 2133 - LAWRENCE
3 59869
EECS 713 High-Speed Digital Circuit Design
Basic concepts and techniques in the design and analysis of high-frequency digital and analog circuits. Topics include: transmission lines, ground and power planes, layer stacking, substrate materials, terminations, vias, component issues, clock distribution, cross-talk, filtering and decoupling, shielding, signal launching. Prerequisite: EECS 312 and senior or graduate standing. EECS 420 recommended. LEC.

The class is not offered for the Spring 2018 semester.

EECS 721 Antennas
Gain, Pattern, and Impedance concepts for antennas. Linear, loop, helical, and aperture antennas (arrays, reflectors, and lenses). Cylindrical and biconical antenna theory. Prerequisite: EECS 360 and EECS 420, or EECS 720, or permission of the instructor. LEC.
Spring 2018
Type Time/Place and Instructor Credit Hours Class #
LEC Stiles, James
MWF 02:00-02:50 PM LEA 3150 - LAWRENCE
3 65768
LEC Stiles, James
MWF 02:00-02:50 PM KS-ST OLTH - EDWARDS
3 68524
EECS 723 Microwave Engineering
Survey of microwave systems, techniques, and hardware. Guided-wave theory, microwave network theory, active and passive microwave components. Prerequisite: EECS 420. LEC.
Spring 2018
Type Time/Place and Instructor Credit Hours Class #
LEC Stiles, James
MWF 09:00-09:50 AM LEA 3150 - LAWRENCE
3 55345
LEC Stiles, James
MWF 09:00-09:50 AM KS-ST OLTH - EDWARDS
3 59779
EECS 725 Introduction to Radar Systems
Basic radar principles and applications. Radar range equation. Pulsed and CW modes of operation for detection, ranging, and extracting Doppler information. Prerequisite: EECS 360, EECS 420, EECS 461. EECS 622 recommended. LEC.
Spring 2018
Type Time/Place and Instructor Credit Hours Class #
LEC Allen, Christopher
TuTh 11:00-12:15 PM LEA 3150 - LAWRENCE
3 59870
LEC Allen, Christopher
TuTh 11:00-12:15 PM KS-ST OLTH - EDWARDS
3 60521
EECS 728 Fiber-optic Measurement and Sensors
The course will focus on fundamental theory and various methods and applications of fiber-optic measurements and sensors. Topics include: optical power and loss measurements, optical spectrum analysis, wavelength measurements, polarization measurements, dispersion measurements, PMD measurements, optical amplifier characterization, OTDR, optical components characterization and industrial applications of fiber-optic sensors. Prerequisite: EECS 628 or equivalent. LEC.

The class is not offered for the Spring 2018 semester.

EECS 738 Machine Learning
"Machine learning is the study of computer algorithms that improve automatically through experience" (Tom Mitchell). This course introduces basic concepts and algorithms in machine learning. A variety of topics such as Bayesian decision theory, dimensionality reduction, clustering, neural networks, hidden Markov models, combining multiple learners, reinforcement learning, Bayesian learning etc. will be covered. Prerequisite: Graduate standing in CS or CoE or consent of instructor. LEC.

The class is not offered for the Spring 2018 semester.

EECS 740 Digital Image Processing
This course gives a hands-on introduction to the fundamentals of digital image processing. Topics include: image formation, image transforms, image enhancement, image restoration, image reconstruction, image compression, and image segmentation. Prerequisite: EECS 672 or EECS 744. LEC.
Spring 2018
Type Time/Place and Instructor Credit Hours Class #
LEC Wang, Guanghui
TuTh 01:00-02:15 PM LEA 1131 - LAWRENCE
3 63594
EECS 769 Information Theory
Information theory is the science of operations on data such as compression, storage, and communication. It is one of the few scientific fields fortunate enough to have an identifiable beginning - Claude Shannon's 1948 paper. The main topics of mutual information, entropy, and relative entropy are essential for students, researchers, and practitioners in such diverse fields as communications, data compression, statistical signal processing, neuroscience, and machine learning. The topics covered in this course include mathematical definitions and properties of information, mutual information, source coding theorem, lossless compression of data, optimal lossless coding, noisy communication channels, channel coding theorem, the source channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, time-varying channels, and network information theory. Prerequisite: EECS 461 or an equivalent undergraduate probability course. LEC.

The class is not offered for the Spring 2018 semester.

EECS 823 Microwave Remote Sensing
Description and analysis of basic microwave remote sensing systems including radars and radiometers as well as the scattering and emission properties of natural targets. Topics covered include plane wave propagation, antennas, radiometers, atmospheric effects, radars, calibrated systems, and remote sensing applications. Prerequisite: EECS 420 and EECS 622. LEC.

The class is not offered for the Spring 2018 semester.

EECS 828 Advanced Fiber-Optic Communications
An advanced course in fiber-optic communications. The course will focus on various important aspects and applications of modern fiber-optic communications, ranging from photonic devices to systems and networks. Topics include: advanced semiconductor laser devices, external optical modulators, optical amplifiers, optical fiber nonlinearities and their impact in WDM and TDM optical systems, polarization effect in fiber-optic systems, optical receivers and high-speed optical system performance evaluation, optical solution systems, lightwave analog video transmission, SONET & ATM optical networking, and advanced multi-access lightwave networks. Prerequisite: EECS 628 or equivalent. LEC.

The class is not offered for the Spring 2018 semester.

EECS 862 Principles of Digital Communication Systems
A study of communication systems using noisy channels. Principal topics are: information and channel capacity, baseband data transmission, digital carrier modulation, error control coding, and digital transmission of analog signals. The course includes a laboratory/computer aided design component integrated into the study of digital communication systems. Prerequisite: EECS 562. Corequisite: EECS 861. LEC.

The class is not offered for the Spring 2018 semester.

EECS 865 Wireless Communication Systems
The theory and practice of the engineering of wireless telecommunication systems. Topics include cellular principles, mobile radio propagation (including indoor and outdoor channels), radio link calculations, fading (including Rayleigh, Rician, and other models), packet radio, equalization, diversity, error correction coding, spread spectrum, multiple access techniques (including time, frequency, and code), and wireless networking. Current topics of interest will be covered. Prerequisite: Corequisite: EECS 861. LEC.

The class is not offered for the Spring 2018 semester.

EECS 869 Error Control Coding
A study of communication channels and the coding problem. An introduction to finite fields and linear block codes such as cyclic, Hamming, Golay, BCH, and Reed-Solomon. Convolutional codes and the Viberbi algorithm are also covered. Other topics include trellis coded modulation, iterative (turbo) codes, LDPC codes. Prerequisite: EECS: 562 or equivalent. LEC.

The class is not offered for the Spring 2018 semester.

EECS 940 Theoretic Foundation of Data Science
A review of statistical and mathematical principles that are utilized in data mining and machine learning research. Covered topics include asymptotic analysis of parameter estimation, sufficient statistics, model selection, information geometry, function approximation and Hilbert spaces. Prerequisite: EECS 738, EECS 837, EECS 844 or equivalent. LEC.

The class is not offered for the Spring 2018 semester.

EECS 820 Advanced Electromagnetics
A theorem-based approach to solving Maxwell's equations for modeling electromagnetic problems encountered in microwave systems, antennas, scattering. Topics include waves, source modeling, Schelkunoff equivalence principle, scattered filed formulations, electromagnetic induction, reciprocity principles, Babinet's principle, and construction of solutions in various coordinate systems. Prerequisite: EECS 420. LEC.

The class is not offered for the Spring 2018 semester.

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