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  • MOOC 
    Signals and Systems, Part 1

    Signals and Systems, Part 1

    We encounter signals and systems extensively in our day-to-day lives, from making a phone call, listening to a song, editing photos, manipulating audio files, using speech recognition softwares like Siri and Google now, to taking EEGs, ECGs and X-Ray images. Each of these involves gathering, storing, transmitting and processing information from the physical world. This course will equip you to deal with these tasks efficiently by learning the basic mathematical framework of signals and systems. This course is divided into two parts. In this part (EE210.1x), we will explore the various properties of signals and systems, characterization of Linear Shift Invariant Systems, convolution and Fourier Transform, while the next part (EE210.2x), will deal with the Sampling theorem, Z-Transform, discrete Fourier transform and Laplace transform. Ideas introduced in this course will be useful in understanding further electrical engineering courses which deal with control systems, communication systems, power systems, digital signal processing, statistical signal analysis and digital message transmission. The concepts taught in this course are also useful to students of other disciplines like mechanical, chemical, aerospace and other branches of engineering and science.

    Course related:
    EE3008A Linear Systems and Signal Processing
    Subjects:
    Electrical Engineering
    Keywords:
    Signal processing
    Resource Type:
    MOOC
     
  • Video 
    Neso Academy

    Neso Academy

    We are on a mission to provide free and subsidized education. We believe that the real world exists beyond the walls of costly institutions. We are here to help you in all the possible ways. A small step to educate the world. Join us and be a part of our creative community. "Every individual is different and talented, what you need are passion and curiosity."

    Course related:
    EE3001A Analogue and Digital Circuits, EE2003A Electronics, EE3008A Linear Systems and Signal Processing, and EE4004A Power Systems
    Subjects:
    Computing, Data Science and Artificial Intelligence, Electrical Engineering, and Electronic and Information Engineering
    Keywords:
    Engineering Engineering -- Data processing Computer science
    Resource Type:
    Video