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4: Signal Processing

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    137364

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    Learning Objectives
    1. Introduce the continuous-time analog signal and its frequency analysis using Laplace transforms.
    2. Discuss discrete-time digital signal and its frequency analysis using both discrete Fourier transforms (DFT) and fast Fourier transforms (FFT). In addition, be familiar with the discrete-time \(z\)-transform of signal and discrete-time system models in \(z\)-transform that is important for digital filter and controller design.
    3. Define signal conversions between analog and digital signals, along with realization hardware for analog-to-digital (A/D) and digital-to-analog (D/A) converters. Understand data conversion between binary and decimal numbers. For graduate-level courses, provide the single and double precision floating-point representation in microprocessors.
    4. Describe low-pass, high-pass, band-pass, and band-kill (notch) filter design for both analog and digital signals. Also describe their implementation and characteristics.
    5. Introduce Nyquist-Shannon sample theory, sample aliasing, and anti-aliasing filter design.
    6. Define the digital interface between the physical and information domains using pulse-train signals such as pulse-width-modulation and frequency modulation methods.
    7. Introduce advanced filter design such as moving average, Chebyshev, and Butterworth filters.

    This chapter introduces the concepts of signal processing in mechatronic systems, including analog-to-digital and digital-to-analog conversions; analog and digital signal frequency responses; low-pass, high-pass, band-pass, and band-kill (notch) filtering; Nyquist-Shannon sample theory; anti-aliasing filtering; and certain advanced filtering techniques.

    Thumbnail: Roots of unity for \(N=4\).

    This page titled 4: Signal Processing was last modified on Mon, 20 Jul 2026 08:10:36 GMT and is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by Guoming Zhu (Co-DREAM OER) .