FIR filters - page 9
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You're overreacting a bit. The speed of light is for electromagnetic waves in a vacuum. In general, it is the speed of propagation of a signal in a medium. And, as people have correctly pointed out, it's quite different for sound.
Oh, great. I thought I said the speed of propagation of sound is different in different mediums. I am used to talking about EMF. so I just gave it to say that the x-axis can be denoted as frequency and it can be denoted as wavelength, and it is connected to each other through a constant. Will that do ?
But first of all you need to understand what is shown on the graph. And for that you need to know what is on the X and Yaxis , and it turns out there is neither frequency nor wavelength, but bars ( X axis . Wikipedia rests :-))), then a legitimate question should arise how we calculate the filter (bandwidth, attenuation, etc.) and use the concept of frequency. And there are bars. How is the number of bars related to frequency ? Who will give us the formula?
You're way out of line, Privalic.
how come there's no wavelength????????????????
it's stated in bars, they don't write discrete readings
of course, for the mass user, they write "bars", which is equivalent to discrete counts.
well, the formula is as follows: look at the wavelengths in bars and calculate the filters
If somebody really needs to know the frequencies (although it is not appropriate for quotations), then they may take the wavelength in bars, multiply by the timeframe in minutes, multiply by 60, i.e. convert it to seconds, then multiply all the data by minus one power and you get Hertz, or rather small fractions of Hertz, which will hardly seem convenient for market cycle evaluation
1 / (wave*TF*60)
it is specified in bars, they will not write discrete counts
of course, for the mass user, they write "bars", which is equivalent to discrete samples.
so the formula is: look at the wavelengths in bars and calculate the filters
If you really need to know the frequencies (though it is not appropriate for quotations), you may take the wavelength in bars, multiply it by the timeframe in minutes, multiply it by 60, i.e. convert it to seconds, then multiply it by minus one power and you get Hertz, or rather small fractions of Hertz, which will hardly be convenient for estimating market cycles
1 / (wave*TF*60)
I absolutely agree.
Yes, representation of frequency by the number of samples may be unusual but it is absolutely correct. F=1/T. T.e. Number of Bars=1/(frequency*sampling interval). If you want to get absolute frequency, you can recalculate. And bars are on the graph. It may be more clear for somebody. But you should always specify the timeframe. For example, 3 bars on 1-minute timeframe correspond to F=1/(3 bara*60sec)=0.005556Hz.
And...you'll laugh a lot... But when I thought in what units to specify the frequency of my filter, I thought that in bars would be more clear.
If you know the timeframe, you know where you put the indicator and the bars, well, here they are in the terminal window. But I wasn't going to use them to study the spectrum. I just wanted to smooth the curve.
Для grasn
Не путайте божий дар с яичницей.
Вот почитайте на досуге. Вам понравиться.
In essence, what is a ban against the pleasure of calling you dear, bad, but very accurate word. It is impossible to determine the exact spectrum for these series, just as it is impossible to calculate the exact ACF, just as it is impossible to get the mathematical expectation, just as many things are impossible. Exactly for these reasons the term "estimation" was introduced. If you suddenly calculate the exact spectrum, you should get a Schnobel Prize. Besides, the Fourier transform is just one of many transforms, no worse and no better in all senses, say, the Laplace transform. You don't get any spectrum, well nobody uses the Fourier transform for such series - it's just proven to be pointless. What you calculate and call a spectrum is rude. Your "wagon and little wagon" came about for a reason.
Exactly the same methods of evaluation of currency quotes, a wagon and a small cart (MA, RSI, MACD etc.), while the quotes are as they are. You may pass them through the phiba.
What does "evaluation of currency quotes by MA" mean? Have you understood what you have written?
Explore...
Thank you very much. Sometimes it's very helpful to forget your stereotypes and look at things from a different perspective.
You guys are arguing about the wrong thing, Prival demonstrates the classical and Sabluk the practical approach. Better let's talk about the applicability of spectral methods to the market. A trend market is low frequency, a flat market is higher frequency. That's understandable to the hedgehog, but how is it "much better" than the same wagons? You can make the flappers long or short too, in principle the flapper is close to a first order Butterworth filter with quality factor 0.7. In most applications it works fine. It's also not a fact that fast response is a good thing, it all depends on the TC.
and the point is that the shape of the frequency response also matters when comparing filters
Low-pass filters have one shape, high-pass filters have another.
Thank you very much. Sometimes it is very useful to forget your stereotypes and look at things from a different perspective.
Always happy to help. I just want to point out that this is not any other side of spectral analysis, but spectral analysis itself. From what I have read electronically (which I can share):
The rest is in hard copy.
F=1/T Only you should always specify on which timeframe. For example 3 bars on a 1 minute timeframe corresponds to F=1/(3 bara*60sec)=0.005556Hz.
And...you'll laugh a lot... But when I thought in what units to specify the frequency of my filter, I thought that in bars would be more clear.
If you know the timeframe, you know where you put the indicator and the bars, well, here they are in the terminal window. But I wasn't going to use them to study the spectrum. I just wanted to smooth the curve.
It starts to clear up what we are dealing with. If you don't mind and have some time, please comment on my reasoning.
Suppose we called, say, 2000 bars in the terminal and want to analyze a "wave" pattern.
May I say that I deal with a wave frequency F=1/T= 1/(2000*timeframe_in_minutes* 60) or with a period of 2000 bars?
It turns out that I can.
Then what can be done with this wave ?
I take it, represent it as a Fourier series and see that this wave with the period of 2000 bars actually consists of a number of harmonics.
Each of the harmonics also has a different frequency/wavelength/period, amplitude.
In other words, each harmonic is again a wave with a period, which is again measured in bars.
If for the filtering process I set a bandwidth for waves from the frequency range,
say from 200 bar to 600 bar, would that mean ? What ?
Always happy to help. I just want to point out that this is not any other side of spectral analysis but spectral analysis itself. From what I read in electronic form (that I can share):
The rest is on paper.
Yes, yes, I was confused by SYNUS.
If you can email me: eugene_dvoskin@yahoo.com
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