Consider a time sinusoid whose time derivative is .
The derivative is larger by a factor and leads by 90 degrees. The ideal differentiator "transfer function" can therefore be expressed in the complex plane as:
Considered in a context of polar coordinates, the magnitude of is the differentiator gain, and the angle is the phase response (with the indicating a shift - see the green line in the above graphic).
Suppose we generate a discrete sine wave by creating waveform samples separated by a time interval ( is an integer).
Then we generate a discrete derivative as follows, using a difference quotient:
This operation has an associated transfer function , which is slightly different from the ideal transfer function . In general, there may be deviations both in the gain and in the phase response. We would like to incorporate both types of error into a single metric, known as "total vector error" (TVE). Define the percentage TVE as follows:
This is effectively the length of the "error vector" divided by the length of the ideal transfer function vector (see graphic).
If ( ) and ( ), what is the total vector error percentage for the discrete differentiator?
Note: For reference, a solution to a similar problem can be found here
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Start with the difference quotient:
y ( k ) = T x ( k ) − x ( k − 1 )
Take the z-transform of both sides and utilize the time-shift property:
Y = T X − z − 1 X X Y = H d = T 1 − z − 1
Substitute in for z :
z = e j ω T j = − 1 ω = 1 2 0 π T = 8 0 0 0 1
The ideal transfer function is (in polar coordinates - second coordinate is the j axis):
H = ( 0 , ω ) = ( 0 , 3 7 6 . 9 9 1 1 )
The transfer function of the discrete differentiator is (in polar coordinates - second coordinate is the j axis):
H d = ( 8 . 8 8 1 0 , 3 7 6 . 8 5 1 6 )
We can see that the actual transfer function is close to the ideal transfer function, but not exactly the same. The percentage TVE turns out to be about 2 . 3 5 6 % . As the processing rate increases (and T decreases), the error tends toward zero.