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Analytic solutionRead more
Created:Dec 07, 2018Last updated:Mar 18, 202153 views0 comments
The pulse length depicted is the deviation from the Fourier pulse length of 170 fs multiplied by the chirp signRead more
Created:Mar 24, 2018Last updated:Apr 29, 202123 views0 comments
PackagesRead more
Created:Jan 24, 2018Last updated:Feb 10, 202126 views0 comments
There are two numbers that are important for FFT resolution: total amount of samples NNN and sampling frequency nnn. If we have fundamental period time TTT, which we may choose to be unity (T=1T=1T=1), then the sampling frequency is simply the amount of samples per unit time, and is called ndt in the code. The sampling frequency is very important: it sets the upper limit on the highest resolvable frequency. By the Nyquist theorem (also known as the Whittaker–Nyquist–Kotelnikov–Shannon theorem,–Shannon_sampling_theorem), for a frequency f0f0f_0 to be resolvable, the sampling frequency has to be at least more than twice that: n>2f0n>2f0n>2f_0. Conversely, with more than two samples, we are able to reconstruct a sine wave perfectly.Read more
Created:Dec 07, 2017Last updated:Mar 25, 202122 views0 comments
Zeitliche Verschiebung kriegen wir durch [Math Processing Error]F′(ω)=exp⁡[−i(ω−ω0)τ0]F(ω), F'(\omega) = \exp\left[-\mathrm{i}(\omega-\omega_0)\tau_0\right]F(\omega), wo [Math Processing Error]τ0\tau_0 is die Verschiebung und [Math Processing Error]ω0\omega_0 das Trägerfrequenz.Read more
Created:Jul 18, 2017Last updated:May 10, 202117 views0 comments
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