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所在平台: Udemy |
课程主页: https://www.udemy.com/course/undergraduate-course-on-signals-systems-ii/
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课程名称：本科信号与系统课程（课程-II） 课程概述：本课程是信号与系统基础系列课程中的第二部分，适合电气、电讯、仪器仪表或生物医学工程专业的学生。理解信号处理和系统分析中的变换理论对于这些专业的学习都是必不可少的。前置课程“本科信号与系统课程-I”是理解本课程的基础，或者学生需具备一定的信号与系统属性及卷积技术的知识。 在本课程中，学生将学习以下内容： 1. **傅里叶级数**：傅里叶级数是一种强大的数学工具，用于将周期信号从连续时间域转换为频率域。它可以将一个周期信号分解为无限多个相关的正弦波成分，反之亦然，通过组合无限个和谐的正弦信号可以合成一个周期信号（通常是非正弦的）。 2. **傅里叶变换**：傅里叶变换是一种强有力的数学工具，用于合成非周期信号。所获得的傅里叶谱在模拟通信技术和模拟滤波器中应用广泛。通过LTI系统的信号处理可以在频率域中进行可视化。 3. **拉普拉斯变换**：拉普拉斯变换是一种简单而强大的数学工具，它为时域信号提供S域表示。拉普拉斯变换能够克服傅里叶技术的一些限制，是控制系统和模拟网络分析的基础。任何系统的传递函数在拉普拉斯域中定义。 4. **采样定理**：采样定理是连接连续模拟信号和离散数字信号的桥梁，为后续离散信号处理课程奠定基础。 作者简介：Udaya Bhaskar先生是一位本科大学级别的教师和GATE培训教师，拥有超过16年的教学经验。他的兴趣领域包括信号处理、半导体、数字设计及其他电子学基础课程。他曾培训数千名学生备战GATE和ESE考试。
This is an undergraduate course on signals and systems. This course is the second part in a series of two courses on basics of signals and systemsFor any electrical, electronics, Instrumentation or bio-medical engineering student applying transformation theory to signal processing and system analysis is necessary. My previous course "undergraduate course on signals and systems-I" is a prerequisite for complete understanding of this course. Or one must have a good knowledge in introductory signals, system properties and Convlution techniques.Fourier series: Fourier series is a powerful mathematical tool that converts a periodic signal in continuous time domain into frequency domain. Fourier series splits up a periodic signal into infinite harmonically related sinusoidal components or inotherwords by combining infinite harmonically related sinusoidal signals a periodic signal(usually non-sinusoidal) can be synthesized.Fourier transform: A power-packed mathematical tool that synthesizes aperiodic signals. The Fourier spectrum obtained here is used in analog communication techniques and in Analog filters. Signal processing through an LTI system can be visualized in frequency domain. Laplace transform: Laplace transform is a simple yet powerful mathematical tool which gives the S-domain representation for a time domain signal. Some of the limitations of Fourier techniques can be overcomed by Laplace transform. Laplace transform is the back-bone of Control systems and Analog network analysis. Transfer function of any system is defined in laplace domain.Sampling theorem: It is a bridge between continuous-analog signals and discrete-digital signals. Sampling theorem lies the foundation for my next coureses in discrete signal processing. About Author:Mr. Udaya Bhaskar is an undergraduate university level faculty and GATE teaching faculty with more than 16 years of teaching experience. His areas of interest are signal processing, semiconductors, digital design and other fundamental subjects of electronics. He trained thousands of students for GATE and ESE examinations.
