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Fundamentals of Electrical Engineering
课程
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英语
96 时
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- 12 序列
- 等级 介绍
课程详情
教学大纲
Elements of signal and system theory
Week 1: Digital and analog information; block diagrams: sources, systems, sinks. Simple signals and systems. Complex numbers.
Analog Signal Processing
Weeks 2-3: Representation of signals by electrical quantities (electric currents and electromagnetic radiation). Elementary circuit theory: resistors and sources, KVL and KCL, power, equivalent circuits. Circuits with memory: impedance, transfer functions, Thévenin and Mayer-Norton equivalent circuits.
Frequency Domain Ideas
Weeks 4-5: Fourier series and Fourier transforms. Signals in time and frequency domains. Encoding information in the frequency domain. Filtering signals. Modeling the speech signal.
Digital Signal Processing
Weeks 6-8: 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.
Communicating information
Weeks 9-10: Fundamentals of communication: channel models, wireline and wireless channels. Analog (AM) communication: modulation and demodulation, noise (signal-to-noise ratio, white noise models), linear filters for noise reduction.
Weeks 11-12: Digital communication: binary signal sets, digital channel models. Entropy and Shannon's Source Coding Theorem: lossless and lossy compression; redundancy. Error-correcting codes: Shannon’s Noisy Channel Coding Theorem, channel capacity, Hamming codes. Comparison of analog and digital communication.
Week 1: Digital and analog information; block diagrams: sources, systems, sinks. Simple signals and systems. Complex numbers.
Analog Signal Processing
Weeks 2-3: Representation of signals by electrical quantities (electric currents and electromagnetic radiation). Elementary circuit theory: resistors and sources, KVL and KCL, power, equivalent circuits. Circuits with memory: impedance, transfer functions, Thévenin and Mayer-Norton equivalent circuits.
Frequency Domain Ideas
Weeks 4-5: Fourier series and Fourier transforms. Signals in time and frequency domains. Encoding information in the frequency domain. Filtering signals. Modeling the speech signal.
Digital Signal Processing
Weeks 6-8: 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.
Communicating information
Weeks 9-10: Fundamentals of communication: channel models, wireline and wireless channels. Analog (AM) communication: modulation and demodulation, noise (signal-to-noise ratio, white noise models), linear filters for noise reduction.
Weeks 11-12: Digital communication: binary signal sets, digital channel models. Entropy and Shannon's Source Coding Theorem: lossless and lossy compression; redundancy. Error-correcting codes: Shannon’s Noisy Channel Coding Theorem, channel capacity, Hamming codes. Comparison of analog and digital communication.
先决条件
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讲师
- Don Johnson
编辑
莱斯大学是一所美国私立研究型大学,位于德克萨斯州休斯敦市。它位于该市的博物馆区,毗邻德克萨斯医学中心。莱斯大学由威廉-马什-莱斯(William Marsh Rice,en)于 1891 年创建,当时名为 "威廉-马什-莱斯文学、科学和艺术发展学院"(The William Marsh Rice Institute for the Advancement of Letters, Science, and Art),1912 年落成,埃德加-奥德尔-洛维特(Edgar Odell Lovett)担任首任校长。
平台
Coursera是一家数字公司,提供由位于加利福尼亚州山景城的计算机教师Andrew Ng和达芙妮科勒斯坦福大学创建的大型开放式在线课程。
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