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Filter Toolkit

FREE Asset 5.0 4.27 4.26 Filter Toolkit 2022-07-13

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LowPass threshold-1920x1080-62b3cfe31908fa338c51c42389baad0d.png


** Help & support on Discord: https://discord.gg/TE7RM5N **


Filter Toolkit is a set of signal filters. These filters can be used to improve the quality of a signal, and to allow an easier process of these signals (accelerometer, gyroscope, magnetometer, etc.).


It includes 8 different filters (ActorComponent) taking a float as input and returning a float:

  • A low-pass filter cutting the signal when the amplitude between two successive samples of the signal is below a threshold
  • A high-pass filter doing the same when the amplitude is above a threshold
  • A mean filter with a customizable size
  • A median filter with a customizable size
  • A derivative filter computing the derivative of a signal
  • A generic kernel filter with a customizable fixed kernel
  • A generic Infinite Impulse Response (IIR) filter
  • A dynamic kernel filter having two inputs: the input value of the signal and the new associated kernel value (allowing you to give more or less weight to an input according to another signal)


And in addition to this, a mean filter for vectors (useful to process the signal from the accelerometer), and a PID controller for more complex systems.


A basic knowledge of signal processing is advised to use this pack.



Technical Details:

Features:

  • Threshold-based low-pass filter
  • Threshold-based high-pass filter
  • Mean filter (for float and Vector)
  • Median filter
  • Generic kernel filter
  • Dynamic kernel filter
  • Generic Infinite Impulse Response filter
  • Derivative filter
  • PID controller

Number of Blueprints: 10

Network Replicated: No

Supported Development Platforms: All platforms

Supported Target Build Platforms: All platforms

Documentation: https://docs.isaratech.com/ue4-blueprints/filter-toolkit

Quick Start Guide: http://isaratech.com/docs/filter-toolkit/quickstart/

Website: http://isaratech.com/

Discord: https://discord.gg/TE7RM5N


Important/Additional Notes: A basic knowledge of signal processing is advised to use this pack.

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