Decorrelation
Decorrelation is a general term for any process that is used to reduce autocorrelation within a signal, or cross-correlation within a set of signals, while preserving other aspects of the signal.[1] A frequently used method of decorrelation is the use of a matched linear filter to reduce the autocorrelation of a signal as far as possible. Since the minimum possible autocorrelation for a given signal energy is achieved by equalising the power spectrum of the signal to be similar to that of a white noise signal, this is often referred to as signal whitening.
Process
Most decorrelation algorithms are
Many data compression algorithms incorporate a decorrelation stage.
By comparison,
Decorrelation techniques can also be used for many other purposes, such as reducing
In
The concept of decorrelation can be applied in many other fields. In neuroscience, decorrelation is used in the analysis of the neural networks in the human visual system. In cryptography, it is used in cipher design (see Decorrelation theory) and in the design of hardware random number generators.
See also
- Equalisation
- Randomness extractor
- Eigenvalue decomposition
- Whitening transformation
References
- ^ "Decorrelation - an overview | ScienceDirect Topics". www.sciencedirect.com. Retrieved 2020-09-25.
- ^ "Data Compression - an overview | ScienceDirect Topics". www.sciencedirect.com. Retrieved 2020-09-25.
External links