Digital Filters (basic explanation) - page 5

 

variation of ftlm-stlm (fatl-rftl & satl-rstl)

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Many people know about Terminator EA created for elite section long time ago.

So, next version of terminator is having the name as C. I. S. M.P-1 EA (using Congestion index, HMA Sniper and weekly pivots and MTF Ichimoku Cross).

Next - Assorted Martingale EA: Schaff Trend nrp and Kama with filter were added.

Next one: Assorted Martingale 2c EA - MTF HiLow Jurik Smooth channel was added.

And the next version of Terminator EA is having the name as Digital Martingale EA.

Why Digital Martingale?

Because this EA is using Mladen's digital indicators which are the same as Digital filters smooth -separate, but removed the MTF:

It is in elite section sorry.

So, I am having some crazy idea: what if we will create public version of this Digital Filters EA using public digital filters indicators?

Just an idea.

 

Any update regarding this?

 



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A digital filter uses a digital processor to perform numerical calculations on sampled values of the signal. The processor may be a general-purpose computer such as a PC, or a specialised DSP (Digital Signal Processor) chip.

The analog input signal must first be sampled and digitised using an ADC (analog to digital converter). The resulting binary numbers, representing successive sampled values of the input signal, are transferred to the processor, which carries out numerical calculations on them. These calculations typically involve multiplying the input values by constants and adding the products together. If necessary, the results of these calculations, which now represent sampled values of the filtered signal, are output through a DAC (digital to analog converter) to convert the signal back to analog form.
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techmac:

Any update regarding this?

Some newer versions were posted here : https://www.mql5.com/en/forum/181008
 
We forecast a single time series using many predictor variables with a new estimator called the three-pass regression filter (3PRF). It is calculated in closed form and conveniently represented as a set of ordinary least squares regressions. 3PRF forecasts converge to the infeasible best forecast when both the time dimension and cross section dimension become large. This requires only specifying the number of relevant factors driving the forecast target, regardless of the total number of common (and potentially irrelevant) factors driving the cross section of predictors. We derive inferential theory in the form of limiting distributions for estimated relevant factors, predictive coefficients and forecasts, and provide consistent standard error estimators. We explore two empirical applications that exemplify the many predictor problem: Forecasting macroeconomic aggregates with a large panel of economic indices, and forecasting stock market aggregates with many individual assets' price-dividend ratios. These, combined with a range of Monte Carlo experiments, demonstrate the 3PRF's forecasting power.
 

Hi to all,


I've decided to study digital signal processing and my reading list is the following:

1. Signals and Systems by Oppenheim et all

2. Discrete-Time Signal Processing by Oppenheim et all

3. Signals, Systems and Inference by Oppenheim et all


My math background: Calculus, linear algebra, differential equations, introductory probability.


I need advises about the following two things:

1. I think that the books in my list are for undergraduates. For moving to graduate/advanced level in signal processing, which books should be added to my reading list?

2. Is my math background sufficient for the graduate/advanced level study? If not, which subject I should consider to add?


Thanks a lot.

 

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