FIR Filter (Window Method) Analysis Object and Template (Digital Filters Option)
You can use this analysis object to filter signals. You can choose between low pass, high pass, bandpass and bandstop with various characteristics.
The object works with Finite Impulse Response (FIR) filters that are calculated using the window method.
Result
The calculated filter coefficients can be output as the result. The result corresponds to the filter's impulse response. In this case, no input data set has to be specified. Alternatively, the result can be a signal that is filtered using the previously calculated FIR filter. For this, a data set to be filtered must be selected on the Data tab. Unlike the filtered signal result, for Filtered signal with phase correction, phase correction takes place using the formula (τ = T/2 (L - 1), if the filter is uneven or τ = LT/2 if the filter is even (L = filter length).
Windows
The window types Rectangular, Bartlett, Hamming, Generalized Hamming, Hanning, Blackman, Kaiser and Chebyshev are available for designing the filter.
Filter Type
The filters can be used as low pass, high pass, bandpass and bandstop.
Specification
Fc or Fc1 and Fc2 are cut-off frequencies of the filter. If you click on the option Use normalized frequencies, all frequency information will be normalized to the sampling frequency. Otherwise, enter the frequencies in the unit that corresponds to the reciprocal value of the time unit of the signal to be filtered. Due to the Nyquist bound, only values up to a maximum of 0.5 or to half of the sampling frequency are permitted.
The filter length determines the steepness of the filter. The longer the filter, the higher the filter steepness. It is possible to specify a fixed length. The filter length can also be estimated for the Kaiser and Chebyshev filter type. In this case, the attenuation and the transition must be specified. The Alpha parameter influences the attenuation behavior of the Generalized Hamming window.