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Course Criteria
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4.00 Credits
Bilmes, Kirchhoff, Ostendorf Introduction to automatic speech processing. Overview of human speech production and perception. Fundamental theory in speech coding, synthesis and reproduction, as well as system design methodologies. Advanced topics include speaker and language identification and adaptation.
Prerequisite:
E E 505; E E 518
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4.00 Credits
Bilmes, Kirchhoff, Ostendorf Introduction to major issues in natural language processing and human language technology, with emphasis on statistical approaches. Addresses topics in statistical parsing and tagging, dialogue systems, information extraction, and machine translation.
Prerequisite:
E E 505
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4.00 Credits
Atlas Digital representation of analog signals. Frequency domain and Z-transforms of digital signals and systems design of digital systems; IIR and FIR filter design techniques, fast Fourier transform algorithms. Sources of error in digital systems. Analysis of noise in digital systems.
Prerequisite:
knowledge of Fourier analysis techniques and graduate standing, or permission of instructor
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4.00 Credits
Atlas Computer systems for acquisition and processing of stochastic signals. Calculation of typical descriptors of such random processes as correlation functions, spectral densities, probability densities. Interpretation of statistical measurements made on a variety of physical systems (e.g., electrical, mechanical, acoustic, nuclear). plus
Prerequisite:
E E 505 or equivalent
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4.00 Credits
Estimation of spectral densities for single and multiple time series. Nonparametric estimation of spectral density, cross-spectral density, and coherency for stationary time series, real and complex spectrum techniques. Bispectrum. Digital filtering techniques. Aliasing, prewhitening. Choice of lag windows and data windows. Use of the fast Fourier transform. The parametric autoregressive spectral density estimate for single and multiple stationary time series. Spectral analysis of nonstationary random processes and for randomly sampled processes. Techniques of robust spectral analysis. Offered: jointly with STAT 520.
Prerequisite:
one of STAT 342, STAT 390, STAT 481, or IND E 315
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3.00 Credits
Marks Multidimensional (MD) signals and systems, MD sampling theorem, sample dependence in higher dimensions, MD FIR filter design using windows and the McClellan transform, MD IIR filter stability and design. Current topics in MD signals and systems.
Prerequisite:
E E 442 or E E 518 or equivalent
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3.00 Credits
Review of spectral analysis. Theory of continuous and discrete wavelets. Multiresolution analysis. Computation of discrete wavelet transform. Time-scale analysis. Wavelet packets. Statistical properties of wavelet signal extraction, smoothers. Estimation of wavelet variance. Offered: jointly with STAT 530; Sp.
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5.00 Credits
Sechen Analyzes how ICbased memory and datapath blocks are designed using static and dynamic CMOS technologies. Gives students extensive experience with industry-standard computer-aided design tools, including Cadence (Virtuoso, DRC, LVS) and Avanti (Hspice). Credit not allowed for both E E 477 and E E 525.
Prerequisite:
E E 476
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4.00 Credits
Helms, Sechen, Soma Ultrahigh speed digital logical families based on output prediction logic; high-speed division; input and output pad design; state-of the-art latch and flip-flop design; clock distribution, including PLLs and DLLs; noise considerations in high-speed digital IC design.
Prerequisite:
E E 477 or E E 525
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4.00 Credits
Darling Principles and techniques used in solid-state e ronics research. Basic familiarity with practices and equipment used oncampus. Laboratory safety; materials handling, storage and disposal; clean room use; photoresist characteristics; mounting, bonding, and probing; wet chemical etching; vacuum evaporation; patterning of metal films using photoresist. Extensive laboratory with limited enrollment.
Prerequisite:
graduate standing and permission of instructor
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