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  1. Another way of saying this is that a periodic signal can be analyzed using a discrete frequency domain.[1]
  2. The inverse Fourier transform converts the frequency domain function back to a time function.[2]
  3. You saw the advantages of using frequency domain data when analyzing the periodicity of a signal.[2]
  4. The Fourier series equation, Equation 3.3, can give us the frequency domain representation of any signal, x(t).[3]
  5. Our usual strategy for transforming a continuous signal into the frequency domain is to first calculate the a and b coefficients, then convert them to C and θ coefficients using Equations 3.6 and 3.7.[3]
  6. Frequency domain representations are particularly useful when analyzing linear systems.[4]
  7. A few periodic signals and their frequency domain representations are illustrated in Figure 5.[4]
  8. Frequency Domain Representation of a Pulse Train Determine the frequency domain representation for the pulse train shown in Figure 6.[4]
  9. Transient signals (i.e. signals that start and end at specific times) can also be represented in the frequency domain using the Fourier transform.[4]
  10. Whereas for the frequency domain, visualization tools such as a spectrum analyzer are commonly in use when visualizing electronic signals.[5]
  11. Also, some specialized signal processing techniques make use of transforms, and this results in a joint time-frequency domain.[5]
  12. In general, using a frequency domain will simplify analysis mathematically for the system running it.[5]
  13. Furthermore, for a mathematical system regulated by linear differential equations, it translates the depiction of a system from that of a time domain to a frequency domain.[5]
  14. The Frequency Domain refers to the analytic space in which mathematical functions or signals are conveyed in terms of frequency, rather than time.[6]
  15. A discipline in which the frequency domain is used for graphical representation is in music.[6]
  16. Often audio producers and engineers display an audio signal within a frequency domain in order to better understand the shape and character of an audio signal.[6]
  17. Low-frequency neural entrainment is often studied using periodically changing stimuli and is analyzed in the frequency domain using the Fourier analysis.[7]
  18. We restrict the frequency-domain analysis method to the Discrete Fourier Transform (DFT), the most classic frequency domain analysis method.[7]
  19. In this section, we describe the frequency domain representation of a periodic neural response is composed of a series of discrete, steady-state event-related responses.[7]
  20. This video introduces the concept of the frequency domain and how it can be used to analyze common AC specifications such as SNR and THD.[8]
  21. In the spectral domain, or frequency domain, the amplitude represents spectral return loss and the phase and its derivatives contain information about the length and dispersiveness of the DUT.[9]
  22. These data were generated by digitizing the interference fringes associated with i s (ω) and i p (ω) in the frequency domain using a 12-bit, 5 mega-sample per second, four channel DAQ card.[9]
  23. The real-valued interference data is digitized in the frequency domain.[9]
  24. This type of processing has the effect of down-sampling the resolution in the frequency domain.[9]
  25. An expression for the response of the stationary ring in the frequency domain is obtained.[10]
  26. To solve this equation, the Volterra frequency domain kernel is derived.[10]
  27. The structural model for analyzing the stationary ring displacement response in the frequency domain is shown in Figure 1 and the symbols are shown in Table 1.[10]
  28. Among them, is called the nth-order generalized frequency-domain response function, also known as the nth-order Volterra frequency domain kernel.[10]
  29. This response is calculated, in the frequency domain, as the sum of the initial displacement v(0) plus the response to a step force –kv(0).[11]
  30. The treatment of initial conditions in the frequency domain, which is necessary for the treatment of the uncoupled linearized equations was initially addressed.[11]
  31. Numerical solutions in the frequency domain show a very good agreement with known ones in the time domain.[11]
  32. The method of nonlinear analysis of MDOF systems is a pseudo-force method in which the uncoupled linearized equations in modal coordinates are solved in the frequency domain.[11]
  33. We derive and show experimentally that optical frequency domain ranging provides a significant SNR gain over time-domain ranging.[12]
  34. A spectrum analyzer takes an analog input signal—a time-domain signal—and uses the Fast Fourier Transform (FFT) to convert it to the frequency domain.[13]
  35. A simple example of frequency domain analysis can be demonstrated by means of the child’s toy shown in ‘A simple linear process’ graphic.[14]
  36. A toy comprised of a weight attached to a handle-mounted spring can illustrate frequency domain analysis.[14]
  37. Most control-design problems that can be solved in this manner can also be solved by direct manipulations in the time domain, but the calculations are generally easier in the frequency domain.[14]
  38. In the frequency domain, you can separate conceptually the sine waves that add to form the complex time-domain signal.[15]
  39. The previous figure shows single frequency components, which spread out in the time domain, as distinct impulses in the frequency domain.[15]
  40. When the same signal is displayed in the frequency domain by an FFT Analyzer, also known as a Dynamic Signal Analyzer, you easily can measure the harmonic frequencies and amplitudes.[15]
  41. The more narrow band the filter used, the more similar the time domain correlation and frequency domain magnitude coherence measures.[16]
  42. You can move Spectrum Time throughout the acquisition to see how the frequency domain view changes over time.[17]
  43. First, for frequency domain analysis, spectrum analyzer controls like center frequency, span and resolution bandwidth (RBW) make it easy to define the spectrum of interest.[17]
  44. Although spectrum analyzers are designed specifically for viewing signals in the frequency domain, they are not always readily available.[17]
  45. This approach enables independent control of the time domain and frequency domain acquisitions, allowing optimization of both waveform and spectrum views of a given signal.[17]
  46. In a frequency domain mooring analysis the wave loads are defined in terms of wave frequency and direction.[18]
  47. This type of analysis demands more computer resources than the frequency domain approach.[18]
  48. The asymptotic properties of the bootstrap in the frequency domain based on Studentized periodogram ordinates are studied.[19]
  49. Fourier transforms provide a mechanism for translating suitable mathematical functions between the time domain and the frequency domain.[20]
  50. This allows another representation in what is called the frequency domain.[21]
  51. What do you see to the right of the combined waves, in the ‘frequency domain’?[21]
  52. There is a strong history of spatial frequency domain approaches to solving the radiative transport equation for light propagation.[22]
  53. In this section, we describe the different aspects of spatial frequency domain acquisition from both the instrumentation point of view and from the acquisition protocol.[22]
  54. However, recent work on improving processing and filtration in the spatial frequency domain has demonstrated significant image quality improvement making such a method viable for clinical use.[22]
  55. Although widely used for imaging purposes, spatial frequency domain measurements can also be performed using a point sensor.[22]

소스

  1. ↑ Frequency domain
  2. ↑ 2.0 2.1 Practical Introduction to Frequency-Domain Analysis
  3. ↑ 3.0 3.1 Frequency Domain Representation - an overview
  4. ↑ 4.0 4.1 4.2 4.3 Time/Frequency Domain
  5. ↑ 5.0 5.1 5.2 5.3 Time Domain Analysis vs Frequency Domain Analysis: A Guide and Comparison
  6. ↑ 6.0 6.1 6.2 Frequency Domain
  7. ↑ 7.0 7.1 7.2 Interpretations of Frequency Domain Analyses of Neural Entrainment: Periodicity, Fundamental Frequency, and Harmonics
  8. ↑ Introduction to Frequency Domain
  9. ↑ 9.0 9.1 9.2 9.3 High resolution optical frequency domain reflectometry for characterization of components and assemblies
  10. ↑ 10.0 10.1 10.2 10.3 Frequency-Domain-Based Nonlinear Response Analysis of Stationary Ring Displacement of Noncontact Mechanical Seal
  11. ↑ 11.0 11.1 11.2 11.3 A frequency-domain pseudo-force method for dynamic structural analysis nonlinear systems and nonproportional damping
  12. ↑ High-speed optical frequency-domain imaging
  13. ↑ Time Domain and Frequency Domain Measurements
  14. ↑ 14.0 14.1 14.2 Frequency Domain Analysis Explained
  15. ↑ 15.0 15.1 15.2 Differences between Frequency Domain and Time Domain
  16. ↑ Time and frequency domain methods for quantifying common modulation of motor unit firing patterns
  17. ↑ 17.0 17.1 17.2 17.3 Spectrum View: A New Approach to Frequency Domain Analysis on Oscilloscopes
  18. ↑ 18.0 18.1 What is the difference between a frequency domain and a time domain mooring analysis?
  19. ↑ Dahlhaus , Janas : A frequency domain bootstrap for ratio statistics in time series analysis
  20. ↑ Frequency-Domain Analysis with DFTs
  21. ↑ 21.0 21.1 4.6 From the time domain to the frequency domain
  22. ↑ 22.0 22.1 22.2 22.3 Spatial frequency domain imaging in 2019: principles, applications, and perspectives

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