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Published:

2019.01.07 12:37

Nonlinear Kalman filter (zm).mq5 (23.93 KB) view

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Theory :

Often we have a need of normalizing some values into known bounds in order to use them in the "oscillator" mode (when we can have a sort of a clear state for a "trend"). One of the possible ways to do that is by using the zero mean method. This version of nonlinear Kalman filter is using a sort of zero mean normalization to make an oscillator out of the filter

Usage :

You can use the color change as signal. There are two possible color change modes :

color change on zero cross
color change on slope change

Nonlinear Kalman filter - floating levels

Singleton Example

This is a working singleton code example. The sole purpose of this post is to provide a working code sample of a singleton object. A singleton object is created when there 'can be only one' of the object. This is accomplished by making an object's constructor private, and ensuring assignment and copy operations are also private. I was working on an EA and identified that an object should never have more than one copy. I don't expect the EA to ever get large enough for it to actually matter that a singleton is used, but I like the clarity in the code for the object's type. The code follows closely the tutorial at http://www.yolinux.com/TUTORIALS/C++Singleton.html.

Zero mean normalized nonlinear Kalman filter - with floating levels

Phase accumulation adaptive bandpass filter

Zero mean normalized nonlinear Kalman filter - indicator for MetaTrader 5