Results 141 to 150 of about 3,435,907 (207)
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Characterising auditory filter nonlinearity
Hearing Research, 1994An important aspect of auditory nonlinearity is that psychoacoustically measured auditory filters broaden as the level at which they are measured increases. However, it is not yet clear whether the change in filter shape is controlled primarily by the level of the probe or that of the masker.
Rosen, Stuart, Baker, Richard
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IEEE Transactions on Neural Networks and Learning Systems, 2020
This brief is concerned with the finite-time tracking control problem for switched nonlinear systems with arbitrary switching and hysteresis input. The neural networks are utilized to cope with the unknown nonlinear functions.
Cheng Fu +3 more
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This brief is concerned with the finite-time tracking control problem for switched nonlinear systems with arbitrary switching and hysteresis input. The neural networks are utilized to cope with the unknown nonlinear functions.
Cheng Fu +3 more
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Neural Systems as Nonlinear Filters
Neural Computation, 2000Experimental data show that biological synapses behave quite differently from the symbolic synapses in all common artificial neural network models. Biological synapses are dynamic; their “weight” changes on a short timescale by several hundred percent in dependence of the past input to the synapse.
Wolfgang Maass 0001, Eduardo D. Sontag
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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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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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Introducing Legendre nonlinear filters
2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014This paper introduces a novel sub-class of linear-in-the-parameters nonlinear filters, the Legendre nonlinear filters. Their basis functions are polynomials, specifically, products of Legendre polynomial expansions of the input signal samples. Legendre nonlinear filters share many of the properties of the recently introduced classes of Fourier ...
Alberto Carini +3 more
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A new class of nonlinear filters-neural filters
IEEE Transactions on Signal Processing, 1993A class of nonlinear filters based on threshold decomposition and neural networks is defined. It is shown that these neural filters include all filters defined either by continuous functions, such as linear finite impulse response (FIR) filters, or by Boolean functions, such as generalized stack filters.
Lin Yin, Jaakko Astola, Yrjö Neuvo
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Journal of Applied Physics, 1953
The theory of optimum nonlinear filters outlined in this paper is based on the consideration of a sequence of classes of nonlinear filters, designated as 𝔑1, 𝔑2, 𝔑3, …, such that each class in the sequence includes all the preceding classes and, furthermore, the class of linear filters is a subclass of every class in the sequence.
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The theory of optimum nonlinear filters outlined in this paper is based on the consideration of a sequence of classes of nonlinear filters, designated as 𝔑1, 𝔑2, 𝔑3, …, such that each class in the sequence includes all the preceding classes and, furthermore, the class of linear filters is a subclass of every class in the sequence.
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at - Automatisierungstechnik, 2019
In this paper, the finite-horizon filtering problem is investigated for a class of nonlinear time-delayed systems with an energy harvesting sensor. We consider a situation where the filter is located in a remote area from the sensor and the transmission ...
Bo Shen +5 more
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In this paper, the finite-horizon filtering problem is investigated for a class of nonlinear time-delayed systems with an energy harvesting sensor. We consider a situation where the filter is located in a remote area from the sensor and the transmission ...
Bo Shen +5 more
semanticscholar +1 more source
Gaussian filter for nonlinear filtering problems
Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002We develop and analyze real-time and accurate filters for nonlinear filtering problems based on the Gaussian distributions. We present the systematic formulation of Gaussian filters and develop efficient and accurate numerical integration of the proposed filter.
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