This chapter considers digital and pulse signals (deterministic or periodic and random-nonperiodic) in the time and frequency domains, which are common origins of EMI emissions from digital systems and natural processes. The chapter also includes the Fourier series and analysis (in trigonometric and complex exponential forms), which are commonly used to analyze and convert time-domain signals to frequency-domain signals and vice versa. On the basis of the spectrum of a trapezoidal signal, the spectrum of the EMI from this signal can be obtained with a solid prediction, as shown in this chapter. Additionally, this chapter introduces the nature of random signals and the definitions of random variables, cumulative distribution functions (CDFs), and probability density functions (PDFs), which are relevant parameters of stochastic signal processes.

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Digital and Pulse Signals, Random Variables, and Stochastic Processes

  • Miroslav Pajovic

摘要

This chapter considers digital and pulse signals (deterministic or periodic and random-nonperiodic) in the time and frequency domains, which are common origins of EMI emissions from digital systems and natural processes. The chapter also includes the Fourier series and analysis (in trigonometric and complex exponential forms), which are commonly used to analyze and convert time-domain signals to frequency-domain signals and vice versa. On the basis of the spectrum of a trapezoidal signal, the spectrum of the EMI from this signal can be obtained with a solid prediction, as shown in this chapter. Additionally, this chapter introduces the nature of random signals and the definitions of random variables, cumulative distribution functions (CDFs), and probability density functions (PDFs), which are relevant parameters of stochastic signal processes.