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Journal of the Optical Society of America A, 1989
A new class of nonlinear matched filters is discussed. These filters involve the transformation of the signal spectrum and the filter transfer function through a nonlinearity before they are multiplied in the transform domain. The resulting filter structures can be considered to be analogous to three-layer neural nets.
O. K. Ersoy, M. Zeng
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A new class of nonlinear matched filters is discussed. These filters involve the transformation of the signal spectrum and the filter transfer function through a nonlinearity before they are multiplied in the transform domain. The resulting filter structures can be considered to be analogous to three-layer neural nets.
O. K. Ersoy, M. Zeng
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Nonlinear filtering with particle filters
2014Convective phenomena in the atmosphere, such as convective storms, are characterized by very fast, intermittent and seemingly stochastic processes. They are thus difficult to predict with Numerical Weather Prediction (NWP) models, and difficult to estimate with data assimilation methods that combine prediction and observations.
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IEEE Transactions on Signal Processing, 1991
A nonlinear filter is introduced whose output is nearest in distance to the output of a FIR (finite impulse response) linear phase filter; hence it is called the NFIR filter. After choosing the impulse response of the FIR filter properly, the NFIR filter can clean impulsive noise and preserve edges of signals.
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A nonlinear filter is introduced whose output is nearest in distance to the output of a FIR (finite impulse response) linear phase filter; hence it is called the NFIR filter. After choosing the impulse response of the FIR filter properly, the NFIR filter can clean impulsive noise and preserve edges of signals.
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IETE Journal of Research, 1976
Optimal nonlinear time invariant filters of three types, viz. the zero memory nonlinearity (ZMNL), the ZMNL followed by a non interacting linearity and the linear device followed by a ZMNL have been discussed on the basis of least mean squared error and maximum signal to noise ratio (matched filter).
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Optimal nonlinear time invariant filters of three types, viz. the zero memory nonlinearity (ZMNL), the ZMNL followed by a non interacting linearity and the linear device followed by a ZMNL have been discussed on the basis of least mean squared error and maximum signal to noise ratio (matched filter).
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The Journal of the Acoustical Society of America, 1973
It has been shown by Flanagan and Landgraf [IEEE Trans. Audio Electroacoust. 16, No. 1, 57–64 (1968)] that in the transformation between glottal area and glottal volume velocity during voiced vowels, the effect of the interaction between the acoustic impedance of the glottis and that of the supraglottal vocal tract cannot always be neglected.
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It has been shown by Flanagan and Landgraf [IEEE Trans. Audio Electroacoust. 16, No. 1, 57–64 (1968)] that in the transformation between glottal area and glottal volume velocity during voiced vowels, the effect of the interaction between the acoustic impedance of the glottis and that of the supraglottal vocal tract cannot always be neglected.
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2018
In this chapter, we will review some of the methods proposed in literature to remove the speckle pattern from ultrasound data based on nonlinear processing. Note that some filters that can also be considered as nonlinear are left aside since they will be deeply treated in other chapters.
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In this chapter, we will review some of the methods proposed in literature to remove the speckle pattern from ultrasound data based on nonlinear processing. Note that some filters that can also be considered as nonlinear are left aside since they will be deeply treated in other chapters.
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Nonlinear multiscale filtering
IEEE Signal Processing Magazine, 2002In this article, we give an overview of scale-spaces and their application to noise suppression and segmentation of 1-D signals and 2-D images. Several prototypical problems serve as our motivation. We review several scale-spaces (linear Gaussian, Perona-Malik, and SIDE-stabilized inverse diffusion equation) and discuss their advantages and ...
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2002
The classic adaptive-filtering algorithms, such as those discussed in the remaining chapters of this book, consist of adapting the coefficients of linear filters in real time. These algorithms have applications in a number of situations where the signals measured in the environment can be well modeled as Gaussian noises applied to linear systems, and ...
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The classic adaptive-filtering algorithms, such as those discussed in the remaining chapters of this book, consist of adapting the coefficients of linear filters in real time. These algorithms have applications in a number of situations where the signals measured in the environment can be well modeled as Gaussian noises applied to linear systems, and ...
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