average filter 예문

예문모바일

The effect is that the quantization error is averaging filter.
An unweighted moving average filter is the simplest convolution filter.
A CIC filter is an efficient implementation of a moving-average filter.
Some implementations of moving average filter are recursive filters but with a finite impulse response.
A moving average filter is commonly used with time series data to smooth out short-term fluctuations and highlight longer-term trends or cycles.
The equivalence of a CIC to moving average filter allows us to trivially calculate its bit growth as N \ log _ 2 ( RM ).
When used with non-time series data, a moving average filters higher frequency components without any specific connection to time, although typically some kind of ordering is implied.
The magnitude plot indicates that the moving-average filter passes low frequencies with a gain near 1 and attenuates high frequencies, and is thus a crude low-pass filter.
The conventional CIC structure is obtained by cascading N identical moving average filters, then rearranging the sections to place all integrators first ( decimator ) or combs first ( interpolator ).
The pole controls the lower limit of frequency and is normally around 0.9 . RASTA-filtering can be changed to use mean subtraction, implementing a moving average filter.
To see this, consider how a moving average filter can be implemented recursively by adding the newest sample x [ n ] to the previous result y [ n-1 ] and subtracting the oldest sample.