[RICE] Fundamentals of Electrical Engineering

Fundamentals of Electrical Engineering
这是rice大学二年级学生开设的一门课，课程大纲如下：
SyllabusHelpElements of signal and system theoryWeek 1:Basics of signals, systems and information
Digital and analog information; block diagrams: sources, systems, sinks. Simple signals and systems. Complex numbers.
Analog signal processingWeek 2: Circuit fundamentals: resistor circuits
Representation of signals by electrical quantities (electric currents and electromagnetic radiation). Elementary circuit theory: resistors and sources, KVL and KCL, power, equivalent circuits.

Week 3: Circuit fundamentals: RLC circuits
Circuits with memory: impedance, transfer functions, Thévenin and Mayer-Norton equivalent circuits.

Frequency domain ideasWeek 4: Fourier Series
Signals in the time and frequency domains. Spectra of periodic signals. Encoding information in the frequency domain. Filtering signals.

Week 5: The Fourier transform
Spectra of non-periodic signals. Filtering signals. Signals in the frequency domain. Modeling the speech signal.

Digital signal processingWeek 6: Signal processing on a computer
Basics of computation. Analog-to-digital (A/D) conversion: Sampling Theorem, amplitude quantization, data rate. Discrete-time signals and systems. Discrete-time Fourier transform, discrete Fourier transform and the fast Fourier transform. Digital implementation of analog filtering.

Week 7: Computing spectra
Discrete-time Fourier transform, discrete Fourier transform and the fast Fourier transform. Computational complexity. Spectrograms.

Week 8: Implementing digital filters
Time- and frequency-domain implementations. Difference equations.

Communicating informationWeek 9: Fundamentals of communication
Channel models, wireline and wireless channels. Noise and interference. Signal-to-noise ratio.

Week 10: Transmitting and receiving information
Analog (AM) communication: modulation and demodulation. Linear filters for noise reduction. Digital communication: binary signal sets, digital channel models.

Week 11: Limits of digital communication
Entropy and Shannon's Source Coding Theorem: lossless and lossy compression; redundancy. Error-correcting codes: Hamming codes.

Week 12: Analog-vs. digital communication Comparison of analog and digital communication. Shannon’s Noisy Channel Coding Theorem, channel capacity.

时间还是蛮长的，希望能坚持下来！


课程链接：https://class.coursera.org/eefun-002