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Locally nonlinear matched filtering
Optics Letters, 1993A new matched filter for pattern recognition is introduced. Previous researchers have introduced matched filters that are nonlinear functions of the spectrum, for which the classical matched filter is divided by some power m of the spectrum of interest.
O, Gualdron, H H, Arsenault
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Toward nonlinear wave digital filters
IEEE Transactions on Signal Processing, 1999The wave digital filter (WDF) theory provides us with a systematic methodology for building digital models of analog filters through the discretization of their individual circuit components. In some situations, WDF principles can also be successfully used for modeling circuits in which a nonlinear circuit element is present under mild conditions on ...
SARTI, AUGUSTO, DE POLI G.
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Benchmarking Nonlinear Filters
2006 IEEE Nonlinear Statistical Signal Processing Workshop, 2006Algorithm developers need relevant and practical criteria to evaluate and compare the performance of different discrete-time filters or filter variants. This paper discusses some pit-falls in different approaches and proposes a combination of criteria on which to base comparisons. A comparison of eight filters for a class of hybrid personal positioning
Niilo Sirola +2 more
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1967
A formal survey of nonlinear filtering with emphasis on some ad hoc truncation schemes.
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A formal survey of nonlinear filtering with emphasis on some ad hoc truncation schemes.
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Signal Processing, 2014
In this paper, two new sub-classes of linear-in-the-parameters nonlinear discrete-time filters, derived from the truncation of multidimensional generalized Fourier series, are presented. The filters, called Fourier nonlinear filters and even mirror Fourier nonlinear filters, are universal approximators for causal, time-invariant, finite-memory ...
Alberto Carini, Giovanni L. Sicuranza
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In this paper, two new sub-classes of linear-in-the-parameters nonlinear discrete-time filters, derived from the truncation of multidimensional generalized Fourier series, are presented. The filters, called Fourier nonlinear filters and even mirror Fourier nonlinear filters, are universal approximators for causal, time-invariant, finite-memory ...
Alberto Carini, Giovanni L. Sicuranza
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IEEE Transactions on Signal Processing, 1997
This paper is composed of two parts. The first part surveys the literature regarding optimum nonlinear filtering from the (continuous-time) stochastic analysis point of view, and the other part explores the impact of recent applications of neural networks (in a discrete-time context) to nonlinear filtering.
S. Haykin, P. Yee, E. Derbez
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This paper is composed of two parts. The first part surveys the literature regarding optimum nonlinear filtering from the (continuous-time) stochastic analysis point of view, and the other part explores the impact of recent applications of neural networks (in a discrete-time context) to nonlinear filtering.
S. Haykin, P. Yee, E. Derbez
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ICASSP '77. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
In conventional filter design there are generally two underlying assumptions. First, it is assumed that the precise nature of the operation to be performed on a signal is known. Second, the signal conditioning is generally a linear operation. (There are certain notable exceptions such as waveform hard-limiting in FM demodulation; but even in this ...
A. Mucciardi, D. Cleveland, E. Orr
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In conventional filter design there are generally two underlying assumptions. First, it is assumed that the precise nature of the operation to be performed on a signal is known. Second, the signal conditioning is generally a linear operation. (There are certain notable exceptions such as waveform hard-limiting in FM demodulation; but even in this ...
A. Mucciardi, D. Cleveland, E. Orr
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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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