Results 271 to 280 of about 230,512 (314)

Permutation filter lattices: a general non-linear filtering framework

IEEE International Conference on Acoustics Speech and Signal Processing, 1993
These lattices define a highly modular and robust class of filters which effectively addresses both the nonlinear characteristics of a system and the possible noise contamination. Permutation filters, much like polynomial filters, are flexible and modular, but instead of having polynomial expansions there are permutation lattice expansions.
Yeong-Taeg Kim, Gonzalo R. Arce
openaire   +2 more sources

Frequency domain non-linear adaptive filter

ICASSP '81. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
A new non-linear adaptive filter is presented. The algorithm is based on the Volterra series implemented in the frequency domain. For a finite memory of length N, the algorithm converges to the equivalent time domain non-linear adaptive filter as proposed by Roy and Sherman [1].
David Mansour, Augustine H. Gray Jr.
openaire   +1 more source

Filters With Small Non-linearities

Twenty-Second Asilomar Conference on Signals, Systems and Computers, 2005
The Kalman filter provides a finite dimensional solution when the signal and observation processes are linear and have Gaussian noise. In this paper the effect of a small non- linearity in the signal is discussed by considering stochastic flows for the signal and a Girsanov transformation for the observation.
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Robust non-linear filtering for video processing

2002 14th International Conference on Digital Signal Processing Proceedings. DSP 2002 (Cat. No.02TH8628), 2003
Noise removal techniques, such as the K-nearest neighbour filter and the /spl alpha/-trimmed mean filter, are known to be very robust in still image noise removal, but they have not been exploited in video processing. We investigate their 3D-extension for use in video sequence noise removal.
Vladimir Zlokolica, Wilfried Philips, Dimitri Van De Ville   +2 more
openaire   +1 more source

QD-an algorithm for non-linear inverse filtering

ICASSP '81. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
Statistical methods for parameter estimation are often based on a Gaussian assumption. In this paper we describe a signal model based on an assumption of uniform distributions. This signal model leads to a simple, non-linear algorithm, called QD, for parameter estimation. The QD algorithm can be applied to adaptive, inverse filtering of speech signals.
Per Hedelin, Gunnar Hult
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A non-linear filtering approach to image matching

Proceedings. Fourteenth International Conference on Pattern Recognition (Cat. No.98EX170), 2002
In this paper we present a novel approach to high precision stereo image matching which employs an iterated extended Kalman filter (IEKF). The matching problem is formulated as a nonlinear filtering problem. We present a state-space representation of the matching problem, and show how nonlinear filtering techniques may be applied to determine optimal ...
John A. Williams 0001, Mohammed Bennamoun   +1 more
openaire   +2 more sources

Anisotropic Filtering of Non‐Linear Surface Features

Computer Graphics Forum, 2004
Abstract A new method for noise removal of arbitrary surfaces meshes is presented which focuses on the preservation and sharpening of non‐linear geometric features such as curved surface regions and feature lines. Our method uses a prescribed mean curvature flow (PMC) for simplicial surfaces which is based on three new contributions: 1.
Klaus Hildebrandt, Konrad Polthier
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The Design of a New Non-linear Predictive Filter

Third International Conference on Natural Computation (ICNC 2007), 2007
The paper presents a new method to design a predictive filter which suits to analyze non-stationary data. The processed data are approximated by polynomial. The approximating function in the paper is cubic spline. The predictive filter is constructed with the true value and the observation value of each observation point.
Xiaoqin Wu, Yanqin Wang, Yaohong Kang
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Laplacian Based Non-Linear Diffusion Filtering

18th International Conference on Pattern Recognition (ICPR'06), 2006
This paper aims to introduce a diffusion filtering based on the Laplacian map. Classical non-linear diffusion filtering using the gradient-map-controlled local diffusivity. The Laplacian maps has similar geometric properties with the gradient map for the extraction of the region boundaries.
Haruhiko Nishiguchi, Atsushi Imiya, Tomoya Sakai 0002   +2 more
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On optimum non-linear extraction and coding filters

IEEE Transactions on Information Theory, 1956
The problem of determining optimal non-linear least-square filters is solved for a class of stationary time series. This theory is then used as the basis for developing a band-width reduction scheme using non-linear encoding and decoding filters, for the same class of signals. A simple illustrative example is included.
A. V. Balakrishnan, Rudolf F. Drenick
openaire   +1 more source