Non-linear multi-dimensional signal processing
Nonlinear multi-dimensional signal processing
In signal processing, nonlinear multidimensional signal processing (NMSP) covers all signal processing using nonlinear multidimensional signals and systems. While multidimensional signal processing is a subset of signal processing (multidimensional signal processing). Nonlinear systems cannot be treated as linear system, using Fourier transformation and wavelet analysis. Nonlinear system will has chaotic behavior, limit circle, steady state, bifurcation, multi-stability and so on. As the complicated of real nonlinear system didn’t have canonical representation, like impose-response of linear systems. Volterra and Wiener series using polynomial integral instead of linear convolution to representation nonlinear systems as the using of this methods naturally extended the signal into multi-dimensional.[1] Multi-dimensional nonlinear filter (MDNF) is also an important part of NMSP, MDNF is always be used to filter noise in real data.
Nonlinear analyser
Multi-dimensional nonlinear filter
Multi-dimensional ensemble empirical mode decomposition method[2]
References
- ^ Liu, H.; Vinh, T. (1991-01-01). "Multi-dimensional signal processing for non-linear structural dynamics". Mechanical Systems and Signal Processing. 5 (1): 61–80. doi:10.1016/0888-3270(91)90015-W.
- ^ Wu, Zhaohua; Huang, Norden E.; Chen, Xianyao (2009-07-01). "The multi-dimensional ensemble empirical mode decomposition method". Advances in Adaptive Data Analysis. 01 (03): 339–372. doi:10.1142/S1793536909000187. ISSN 1793-5369.