Examples of using Finite impulse response in English and their translations into Bulgarian
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Finite impulse response(FIR).
Example: Digital filter with finite impulse response.
Finite impulse response Hilbert transforms are very easy to derive.
Manifestation of the Gibbs phenomenon with finite impulse response filters.
Phase response of a finite impulse response filter with symmetric coefficients.
Consider a window w(k)defined in discrete time and applied to a finite impulse response filter.
We can derive a simple good finite impulse response low pass filter in one of two ways.
An interesting manifestation of Gibbs phenomenon can be seen when designing equalizers based on finite impulse response filters.
If the filter is a finite impulse response(FIR) one, constantly computing its coefficients will be slow.
The discrete Fourier transform and finite impulse response filters.
Say that this is a finite impulse response digital filter with length N and weights a(k) and a transfer function H(z).
Example: Frequency response of a finite impulse response filter.
Finite impulse response filters exhibit the Gibbs phenomenon, which means that they have ripples close to the cutoff frequency.
The general transfer function of a finite impulse response filter then is.
For example, a good finite impulse response filter uses a generalized form of the inverse Fourier transform and not the inverse transform itself.
The following picture shows the typical magnitude response of a digital finite impulse response low pass filter.
In the general complex number case, finite impulse response all pass filters have the transfer function.
Finite impulse response(FIR) and infinite impulse response(IIR) filters that work as or at least approximate discrete Hilbert transforms exist.
These filterbanks may contain either finite impulse response(FIR) or infinite impulse response(IIR) filters.
Taking the Z transform of both sides,we can compute the general form of the transfer function of a finite impulse response filter. It is the following.
Alternatively, the magnitude response of the finite impulse response filter is the frequency content of the filter of length N.
Finite impulse response all pass filters then are used for filter transformations- to transform a FIR low pass filter into a FIR high pass filter.
An orthogonal wavelet is entirely defined by the scaling filter- a low-pass finite impulse response(FIR) filter of length 2N and sum 1.
The magnitude response of a typical finite impulse response low pass filter is in fact a Fourier series approximation of the desired magnitude response. .
The smaller the value of ω0 in the Dolph-Chebychev window, the more this function resembles an impulse andacts similarly to an all pass filter on the magnitude response of a finite impulse response filter.
There are slight modifications to using the transform to derive finite impulse response filters or to gage the performance of these filters.
Finite impulse response filters, for example, are simpler, as they compute the output signal y(k) only from the samples of the input signal x(k) and therefore set ai= 0 for all i.
Suppose that we take the sampling frequency offs= 2000 Hz and we create a standard finite impulse response low pass filter with length N= 101 and cutoff frequency of fc= 40 Hz.
A finite impulse response equiripple filter can be designed with successive iterations between the forward and inverse discrete Fourier transform(DFT).
There are various DSP operations and the discussion below applies to all, although when engineers talk about DSP errors,they usually discuss filters- finite impulse response filters, infinite impulse response filters, etc.