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Course Criteria
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3.00 Credits
This course contains the fundamental theory required to design adaptive systems. Topics include parameter identification, ARMA modeling, model reference systems, model algorithmic control, self-tuning systems, and adaptive filtering. Applications to physical and physiological systems are introduced. Prerequisites/Corequisites: Prerequisite: ECSE 6400 or equivalent. When Offered: Spring term odd-numbered years. Cross Listed: Cross-listed as BMED 6480. Students cannot receive credit for both this course and BMED 6480. Credit Hours: 3
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3.00 Credits
This course introduces methods that leverage the basic analysis techniques learned in Robotics I to develop numerical and algorithmic techniques needed to endow robots with the "intelligence" to devise strategies to solve problems they will encounter. Once these abilities are sufficiently well developed, robots will become safe and autonomous, thus paving the way for pervasive personal robots. Topics include: configuration space representation, cell decomposition, roadmap methods, rapidly-exploring random trees, simultaneous localization and mapping, contact modeling, grasping, and dexterous manipulation.Prerequisites/Corequisites: Prerequisite: ECSE 4480 or CSCI 4480. When Offered: Spring term. Cross Listed: Cross-listed as ECSE 4490, CSCI 4490 and CSCI 6490. Students cannot receive credit for both this course and ECSE 4490, CSCI 4490 or CSCI 6490. Credit Hours: 3
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3.00 Credits
Deterministic signal representations and analysis, introduction to random processes and spectral analysis, correlation function and power spectral density of stationary processes, noise mechanisms, the Gaussian and Poisson processes. Markov processes, the analysis of linear and nonlinear systems with random inputs, stochastic signal representations, orthogonal expansions, the Karhunen-Loeve series, channel characterization, introduction to signal detection, linear mean-square filtering, the orthogonality principle, optimum Wiener and Kalman filtering, modulation theory, and systems analysis. Prerequisites/Corequisites: Prerequisites: ECSE 2410 and ECSE 4500 or equivalent. When Offered: Fall term annually. Credit Hours: 3
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3.00 Credits
Classical statistical decision theory, decision criteria, binary and composite hypothesis tests. Statistical models of signals and noise. Detection of known signals in Gaussian noise. Receiver operating characteristics and error probability. Applications to radar and communications. Detection of signals with unknown or random parameters, detection of stochastic signals, nonparametric detection techniques. Statistical estimation theory, performance measures. Cramer-Rao bounds, estimation of unknown signal parameters, optimum demodulation, signal design. Prerequisites/Corequisites: Prerequisites: probability theory and ECSE 6510. When Offered: Spring term annually. . Credit Hours: 3
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3.00 Credits
Information measures, characterization of information sources, coding for discrete sources, the noiseless coding theorems, construction of Huffman codes. Discrete channel characterization, channel capacity, noisy-channel coding theorems, reliability exponents. Various error-control coding and decoding techniques, including block and convolutional codes. Introduction to waveform channels and rate distortion theory. Prerequisites/Corequisites: Prerequisite: probability theory. Corequisite: ECSE 6510. When Offered: Fall term annually. Credit Hours: 3
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3.00 Credits
Review of measure and integration theory, elements of probability, random variables, conditional probability, and expectations. Stochastic processes, stationarity and ergodicity. Gaussian processes and Brownian motion, the Poisson process. Markov processes, wide-sense stationary processes, spectral representations, linear prediction and filtering. Stochastic integrals and differential equations, white noise and the stochastic calculus, the Fokker-Planck equation, diffusion processes, recursive filtering and estimation, evaluation of likelihood ratios. Applications in communication, information processing, and control. Prerequisites/Corequisites: Prerequisite: ECSE 6510. When Offered: Fall term on sufficient demand. Credit Hours: 3
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3.00 Credits
The functional characterization of digital signals and transmission facilities, band-limited and duration-limited signals, modulation and demodulation techniques for digital signals, error probability, intersymbol interference and its effects, equalization and optimization of baseband binary and M-ary signaling systems, error control coding techniques, digital filtering current practices in modern design. Introduction to communication networks and switched systems, store-and-forward communication systems, broadband communication techniques, channel protocol, current developments in digital communication systems design and operation. Prerequisites/Corequisites: Prerequisites: ECSE 4520, linear systems theory and transform theory. When Offered: Fall term annually. Credit Hours: 3
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3.00 Credits
Principles of efficient digital representation of analog signals and their application to images, audio, and multimedia signals. Topics include rate-distortion theory, scalar and vector quantization, trellis-coded quantization (TCQ), entropy coding, Huffman coding, arithmetic coding, bit-plane coding, set partition coding, Ziv-Lempel coding, PCM, DPCM, transform coding, subband/wavelet coding, and tree/trellis coding. Certain standard or oft-used systems, evolving or current, such as JPEG, JPEG2000, JPEG-LS, Wavelet/TCQ, EZW, SPIHT, FBI Fingerprint, and MPEG will be treated. Prerequisites/Corequisites: Prerequisites: ECSE 6510, ECSE 6530. When Offered: Spring term odd-numbered years. Credit Hours: 3
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3.00 Credits
Review of the discrete Gaussian noise channel and development of coding theorems. Waveform channels, orthonormal expansions of signals and Gaussian noise, the vector model of waveform channels, time-bandwidth and dimensionality, optimum receiver principles, channel capacity and reliability functions, signal design and selection. Coding for the Gaussian noise channel, theoretical performance bounds, implementation of error control coding, techniques for overall system evaluation, investigation of fundamental rate versus reliability tradeoffs. Prerequisites/Corequisites: Prerequisite: ECSE 6510. When Offered: Spring term annually. Credit Hours: 3
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3.00 Credits
A comprehensive description of the concepts used in modern wireless and cellular systems. The general topics covered will be wireless channel models, multi-access issues, such as FDMA/TDMA and CDMA with a brief view of GSM, descriptions of digital transmission methods in wireless, receiver diversity, channel estimation and multi-user detection, and wideband communications. We will address the topics of system capacity and the effects of automatic power control, wireless networks, and DSP applications for wireless. Prerequisites/Corequisites: Prerequisites: ECSE 6510 and ECSE 6560. When Offered: Spring term annually. Credit Hours: 3
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