Noise Cancellation Using QRD RLS Algorithms


This application note aims to simulate a noise cancellation problem with MATLAB tools. This is purposed for pre-processing process for final gesture recognition application. It also shows advantages and disadvantages of an approach used for a noise cancellation. In applications for gesture recognition the signals can reflect and be detected not only from a desired source (a hand), but from the environment as well, which creates undesired noise and hardens the process of precise gesture identification.

Therefore, it is essential to eliminate the signals, which come from other static sources than a hand. For these purposes echo cancellation methods can be used. Echo cancellation is widely and successfully applied in telephony in a way of preventing echo from being created or removing it after it is already present. We will assume that a hand will appear just for a short time period and the additional reflections will act as an additional short period "disturbance".

The echo cancellation in this specific case will be based on QRD algorithm with double precision arithmetic and exponential forgetting. The QRD algorithm is also called as an information filter without square root operations. It is based on QRD decomposition of the input/output information matrix. The recursively updated QRD factorization of the information matrix helps to avoid the problem with loss of positive definiteness of the information matrix due to rounding errors and, thus, provides a numerically stable solution.

Package Summary

Title Noise Cancellation Using QRD RLS Algorithms
License app_note.pdf for licensing conditions.
Package content Simulation package for modelling of echo cancellation for ultra-sound hand-gesture recognition in form of MATLAB scripts or compiled Win 64bit applications.
Size ZIP file: 5621482 Bytes
PDF file: 3137966 Bytes
Required tools
& platform
MATLAB 2018b or Win7 64bit or Win10 64bit
Installation notes See app_note.pdf

Result Category

Project number Year RIV category Comment
8A17006 2018 Gfunk Functional sample (demo)

Contact Person

Please, do not hesitate to contact Raissa Likhonina to obtain more information.