What is the knee frequency?
The knee point on a frequency response curve. The traditional concept was that instrument bandwidth should be five times the signal to be observed. The maximum frequency component of the signal being tested is known as the knee frequency.
Which frequency domain represents a square wave?
The ideal square wave contains only components of odd-integer harmonic frequencies (of the form 2π(2k − 1)f). Sawtooth waves and real-world signals contain all integer harmonics. A curiosity of the convergence of the Fourier series representation of the square wave is the Gibbs phenomenon.
How do you measure knee frequency?
The formula [X. sub. L] = 2[pi]fL provides the expression for inductive reactance, but here f is the knee frequency which is defined as 0.5/Tr, Tr = rise time.
What is the bandwidth of a square wave?
Real square-waves have a finite rise and fall time of course and the bandwidth is related to that time. This required bandwidth is approximately 0.35 / Tr where Tr is the rise-time (or fall-time) measured between the 10% to 90% of the square-wave amplitude.
Why are digital waves more reliable?
Digital signals are a more reliable form of transmitting information because an error in the amplitude or frequency value would have to be very large in order to cause a jump to a different value. Signals are composed of infinite possible values. Sound signals can vary smoothly in volume and pitch.
What does knee frequency mean in clock signals?
Apparently, knee frequency means something different — I did not know that. When I looked into the Johnson & Graham’s book ( as jallem suggested ), I did see a different definition that has do with the spectrum of clock signals with finite rise/fall times. change ( a square wave, I mean) from 0 to 1. The ratio knee/3-dB frequencies
How is the knee frequency described in black magic?
This knee frequency is described in “High Speed Digital Design: A Handbook of Black Magic” as the point at which the spectrum of a real signal would show a steep fall off. I simulated this, first with python and then LTspice, and expected that the spectrum would be monotonously decrease above the knee frequency.
Which is the steepest rise in knee frequency?
The green spectrum has the steepest rise time (10 ps), whilst blue has a lower (100 ps) and red the lowest (1000 ps). One can see that the spectrum of blue shows a steep fall off somewhere around the knee frequency (light blue shows knee frequency), but then rise again (black arrows).
How is the Fourier frequency of a square wave calculated?
Lets take a 1 hz square wave. The signal goes from zero to 100% [1] in an instant. Then will remain at 1 for 1/2 of the wave length or 500ms. Then it goes negative to -1 and remains there for 500ms. And the cycle repeats. So, it is + for half the time and – for the other half. It’s the rise/fall that must be infinite.