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| Electrical Engineering |
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650-723-3931
Session dates and times for courses are available in Axess under the Guest Menu. Course day, time, and units are subject to change. Courses are eight weeks long unless otherwise noted in the course description or details.
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Signal Processing and Linear Systems II |
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The Fourier Transform and its Applications |
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Digital Signal Processing |
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Introduction to Statistical Signal Processing |
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Seminar on Computer Systems |
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Robust and Testable Systems Seminar |
EE 102B
Signal Processing and Linear Systems II
4
units
Time: see http://axess.stanford.edu
Concepts and mathematical tools in discrete-time signal processing and linear systems analysis with examples from digital signal processing, communications, and control. Discrete-time signal models. Continuous-discrete-continuous signal conversion. Discrete-time impulse and step response. Frequency domain representations: Fourier series and transforms. Connection between continuous and discrete time frequency representations. Discrete Fourier transform (DFT) and fast Fourier transform (FFT). Digital filter and signal processing examples. Discrete-time and hybrid linear systems. Stability and causality. Z transforms and their connection to Laplace transforms. Frequency response of discrete-time systems. Discrete-time control.
Prerequisite: EE 102A.
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EE 261
The Fourier Transform and its Applications
3
units
Time: see http://axess.stanford.edu
The Fourier transform as a tool for solving physical problems. Fourier series, the Fourier transform of continuous and discrete signals and its properties. The Dirac delta, distributions, and generalized transforms. Convolutions and correlations and applications; probability distributions, sampling theory, filters, and analysis of linear systems. The discrete Fourier transform and the FFT algorithm. Multidimensional Fourier transform and use in imaging. Further applications to optics, crystallography. Emphasis is on relating the theoretical principles to solving practical engineering and science problems.
Prerequisite: Fourier series at the level of 102A, and linear algebra.
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EE 264
Digital Signal Processing
3
units
Time: see http://axess.stanford.edu
Two sided Z-transform. Linear time invariant discrete time systems. Sampling theory; A/D and D/A conversion. Analog and digital filter design. Quantization of signals and filter conefficients. Signal scaling. DFS, DFT, and sampling in the frequency domain. Interpolation and decimation. Oversampling techniques for ADC and DAC. Digital signal processing for wireless communications.
Prerequisite: EE 102B. Recommended: EE 261, EE 278.
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EE 278
Introduction to Statistical Signal Processing
3
units
Time: see http://axess.stanford.edu
Random variables, vectors, and processes; convergence and limit theorems; IID, independent increment, Markov, and Gaussian random processes; stationary random processes; autocorrelation and power spectral density; mean square error estimation, detection, and linear estimation.
Prerequisite: EE 178 or STATS 116, and linear systems and Fourier transforms at the level of 102A,B or 261.
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EE 380
Seminar on Computer Systems
1 unit
Time: see http://axess.stanford.edu
Current research in the design, implementation, analysis, and use of computer systems from integrated circuits to operating systems and programming languages.
Note: See this web site for Stanford On line: http://cetus.stanford.edu/onlineclass.aspx
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EE 385A
Robust and Testable Systems Seminar
1-4
units
Time: see http://axess.stanford.edu
Student/faculty discussions of research problems in the design of reliable digital systems. Areas: fault-tolerant systems, design for testability, production testing, and system reliability. Emphasis is on student presentations and Ph.D. thesis research.
Prerequisite: Consent of instructor.
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