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All rights reserved. The filtering of DFT ideal filter itself is known method, can have: ideal bandpass filter, ideal highpass filter, ideal low-pass filter, desirable rejection filter.
And phase function is carried out the filtering of DFT ideal filter, be innovation of the present invention. The 3rd step: calculate output function y r t ,.
Also promptly two discrete series pointwises are multiplied each other, obtain consequent discrete series. The 3rd step also was innovation of the present invention. By above-mentioned steps, obtain the digital signal y of one seasonal effect in time series process filtering r t. Except above-mentioned basic step, when practical application, can also increase step:. In the described first step, carry out before the Hilbert transform, earlier to x r t carry out pre-service.
In described the 2nd A step, calculate after the instantaneous envelope, again a t is modified processing. Described to x r t carry out pre-service, comprise in the following processing mode one or more:. Pick wild value, equilibrium, conventional filtering;. Above-mentioned conventional filtering comprises: conventional belt pass filter, conventional high-pass filtering, conventional low-pass filtering, conventional bandreject filtering, wavelet transform filtering, smothing filtering;.
Above-mentioned smothing filtering comprises: wavenumber filtering, medium filtering, integral filtering. Described a t is modified processing, comprises in the following processing mode one or more:.
Medium filtering, integral filtering, wavenumber filtering. These pre-service, modification processing mode all are known technology means commonly used in the filtering, use these technological means in technical scheme of the present invention, can improve filter effect better at the concrete applicable cases of difference.
For example above-mentioned means can be used in combination:. In the described first step, carry out before the Hilbert transform, earlier to x r t carry out pre-service, described pre-service comprises one or more in the following processing mode: pick wild value, equilibrium, conventional belt pass filter, conventional high-pass filtering, conventional low-pass filtering, conventional bandreject filtering, wavelet transform filtering, wavenumber filtering, medium filtering, integral filtering;.
In described the 2nd A step, calculate after the instantaneous envelope, again a t is modified processing, described modification processing comprises one or more in the following processing mode: medium filtering, integral filtering, wavenumber filtering;. Go on foot the 2nd small step at described the 2nd B, described DFT ideal filter is one of following: ideal bandpass filter, ideal highpass filter, ideal low-pass filter, desirable rejection filter.
The invention has the beneficial effects as follows:. Make filtering performance better, can suppress unwanted frequency band signals as far as possible. Basically there is not simultaneously this effect of jeep. Figure 10 is the Figure 11 is the spectrum diagram of Figure 10 recording channel.
Figure 12 has the conventional belt bandpass filter of 3Hz fringing to x r t filtering output synoptic diagram. Figure 13 is the spectrum diagram of Figure Further describe the present invention below in conjunction with embodiment.
Scope of the present invention is not subjected to the restriction of these embodiment, and scope of the present invention proposes in claims. The physical record road of one digital signal is designated as x r t. Would it be possible to describe what exactly are you trying to achieve? Sorry for being a bit confusing. You just have to convolve the two sequences.
So what should I do after using fourier transform on both the H z and x n? Can I please ask if this is some kind of homework where you have been asked to "emulate" the way that function operates? Show 3 more comments. Active Oldest Votes. Choosing a finite FFT length is the equivalent to truncating the impulse response. Improve this answer. Hilmar Hilmar 26k 1 1 gold badge 19 19 silver badges 41 41 bronze badges. Thank you. What I'm trying to solve is how can you implement an IIR filter in the frequency domain.
Since filter function in the matlab can actually handle an IIR or FIR system since its contents do time domain filtering convolution , this rises up to why I'm curious about the IIR filtering in the time domain. How can you do that? Thanks for any help. I tried running the function he made but got different outputs compared to the filter function. It's slower, less precise, has higher latency and requires way more memory. I can't think of a case where a direct time domain, when done properly, isn't much better.
Convolution is only applicable to FIR filters. Yes I know it's not practical in real life applications, I just wanted to know the theory behind it by making a function for it.
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