NEEC 6501 Random Processes for Engineering Applications (3 sem. cr.)
Communication systems and computer networks are designed to provide high performance consistently and reliably in the presence of noisy communication channels; equipment faults; a wide range of media applications that combine voice, images and video; and high variability in user demand. Probability models provide the mathematical framework for characterizing random variability and form the basis for tools to design systems that perform predictably in the face of random inputs and environments. Students review the notion of a random variable and its characterization using a probability distribution function and associated moments. They focus on characterizing the joint behavior of multiple random variables to understand their interdependence and to enable prediction of likely outcomes. The joint distribution function as well as the correlation and the covariance functions are essential tools in achieving these objectives. The notion of a random process, consisting of a sequence and even a continuum of random variables, is introduced, and the probability tools are extended to capture joint behavior. Random processes are shown to describe signals and dynamic behavior encountered in engineering systems. The utility of probability models is demonstrated through applications in communication systems, reliability, digital signal processing, and communications networks.

 

NEEC 6521 Communications Systems I (3 sem. cr.)
Communication systems are at the heart of today’s information-driven economy and support our modern-day lifestyles and even our very existence. From the familiar telephone that was invented over a century ago to modern-day cell phones, wireless networks, and the Internet, as well as radio, television, cable, and satellite systems, we rely on electrical communication systems in almost all aspects of our lives. This course focuses on the technologies underlying these systems, which constitute the field of digital communications. Topics include digital transmission and reception, signal space representations, spectral analysis of digitally modulated waveforms, channel equalization, introductory concepts of information theory, and error correction coding.

 

NEEC 6525 Wireless Networks (3 sem. cr.)
This course describes wireless networking protocols, architectures, and technologies. It covers all protocol layers, with an emphasis on medium access control and network layer topics. Students examine concepts and specific standards for wireless personal area networks, including Bluetooth and IEEE 802.15; wireless local area networks, including the IEEE 802.11 family of standards; and wireless metropolitan area networks, including cellular systems and IEEE 802.16. They also learn about concepts and specific methods that enable mobile networking, including Mobile IP, and mobile ad-hoc network (MANET) routing protocols. The course also introduces students to emerging systems that utilize wireless networking, such as sensor networks and pervasive computing.

 

NEEC 6551 Digital Signal Processing I (3 sem. cr.)
This course introduces students to the concepts, techniques, and applications of digital signal processing (DSP) via the context of a real-time DSP system for the filtering of analog signals. The central relationship of a digital filter’s frequency response to the frequency response of an equivalent analog filter is established using time and frequency domain models for analog-to-digital and digital-to-analog conversion. A discussion of oversampling as a means of shifting the workload in a real-time DSP system from analog to digital filtering is used to introduce detailed time and frequency domain models of downsampling and upsampling. Techniques for the design of a digital filter’s frequency response are presented in view of the various trade-offs (e.g., linear phase, arithmetic complexity, coefficient quantization, arithmetic quantization) between practically realizable implementations of infinite impulse response and finite impulse response filters. The Discrete Fourier Transform (DFT)and Fast Fourier Transform algorithms are introduced as a practical means of frequency analysis, particularly in the context of examining a digital filter’s frequency response during the design process. The relationship of the DFT to the multidimensional DFT, the Discrete Cosine Transform, the Time-Dependent Fourier Transform, and the Complex Cepstrum are also discussed.

 

NEEC 6552 Digital Signal Processing II (3 sem. cr.)
In this course, advanced perspectives on fundamental digital signal processing (DSP) topics are formulated, studied, and utilized for the conceptual analysis of specialized DSP techniques in selected areas. The Discrete-Time Fourier Transform and the Discrete Fourier Transform (DFT) are examined from the perspective of Discrete Hilbert Transform relations. The Fast Fourier Transform is studied from the perspective of alternative computational structures with differing properties. Digital upsampling and digital downsampling are viewed from the perspective of efficient multirate systems for fractional decimation. Filter banks are generalized beyond the traditional uniform DFT filter bank. Specialized topics addressed include quadratic time-frequency distributions, wavelets and wavelet transforms, two-dimensional infinite impulse response filters, different formulations of the Discrete Cosine Transform, the periodogram and the averaged periodogram for spectral analysis, parametric signal modeling using the autocorrelation method, and computational alternatives for the Complex Cepstrum.

 

NEEC 6557 VLSI Signal Processing (3 sem. cr.)
This course aims to convey knowledge of advanced concepts in VLSI signal processing. Emphasis is on the architectural exploration, design, and optimization of signal processing systems for communications, with focus on the exciting and exploding field of systems for wireless communications. The basic principles are applied to architectural exploration and implementation of complete wireless systems, including all aspects of the design problems such as analog digital trade-offs, synchronization, modulation, equalization, and error correction.

 

NEEC 6993 Independent Study (1–3 sem. cr.)
Students complete an independent study on an electrical engineering topic with course objectives determined in consultation with a supervising instructor.

 

NEEC 6994 Directed Research (1–3 sem. cr.)
Students research an area of electrical engineering under the supervision of an instructor. The research problem is determined in consultation with the supervising instructor.

 

NEEC 8591 Special Topics: Organization and Management of Ad-Hoc Sensor and Actuator Networks (3 sem. cr.)
Wireless sensor and actuator networks are rapidly gaining major traction in a wide range of application areas. To be truly successful in the commercial arena, however, the individual transceiver nodes must be tiny, easily integratable into the environment, and inexpensive. Most importantly, they must be self-contained in terms of energy: via a one-time battery charge or a replenishable supply of energy scavenged from the environment. In this seminar series, students traverse the wireless sensor and actuator paradigm in a bottom-up fashion. Starting from implementation constraints and properties of the wireless medium, they explore the trade-offs at all layers of the abstraction hierarchy up to the application layer, using metrics such as energy efficiency, robustness, and ease of deployment. 

 

NEEC 8997 Thesis (3 sem. cr.)
Students may conduct thesis research to complete the M.S. in Electrical Engineering program, in lieu of general elective courses. Students may register for this course for a maximum of two semesters, for a total of six semester credits.