Results 151 to 160 of about 1,171,117 (197)

Adaptation and gain normalization

Proceedings of the Royal Society of London. Series B. Biological Sciences, 1982
It has been suggested in the past that adaptation effects may serve a useful role in perception. This paper shows that if the adaptation process follows a simple scheme, called proportional gain adjustment, then it can fulfil two useful functions : correction of errors and recalibration. The proposed scheme controls the gain of the system.
S, Ullman, G, Schechtman
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Gain adaptive tracking

Journal of Guidance, Control, and Dynamics, 1993
Properly joining the different modes of a multiregime tracker is difficult. This paper describes a novel, image-based algorithm for tracking a maneuvering target. The form of the algorithm is like the extended Kalman filter, but the gain adjustment utilizes image information in a sophisticated manner to better compute the error covariance.
D. Sworder, R. Vojak, R. G. Hutchins
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Adaptive gain control

1970 IEEE Symposium on Adaptive Processes (9th) Decision and Control, 1970
Communications and radar receivers of advanced design may utilize real time computers for signal processing. In such instances an adaptive learning scheme can be employed to optimize use of the receiver's dynamic range. An adaptive algorithm for statistically optimum AGC is derived in which the receiver gain is adjusted during the learning process so ...
Chia-pu Wang, Stephen Rappaport
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Adaptive gain networks

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 1994
We propose several neuron models featuring adaptive gain parameters in addition to the weights. These are shown to enhance learning speed on parity problems of various sizes. >
C.W. Codrington, M.F. Tenorio
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More on Gain Adaptive Tracking

Journal of Guidance, Control, and Dynamics, 1997
The polymorphic estimator algorithm proposed by the first author, \textit{R. Vojak} and \textit{R. G. Hutchins} [J. Guid. Control Dyn. 16, 865-873 (1993)] is modified in order to improve the tracking performance in the presence of discontinuities. The novelty of the approach results from the measurement architectures. This algorithm is shown by example
Sworder, D. D., Boyd, J. E.
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Adaptive gain control (Corresp.)

IEEE Transactions on Information Theory, 1971
A Bayesian learning algorithm for statistically optimum adaptive gain control (AGC) is derived in which the receiver gain is adjusted during the learning process so that the average cost of excluding the received signal from the receiver's dynamic range is minimized.
null Chia-Pu Wang, S. Rappaport
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Contrast adaptation and contrast gain control

Experimental Brain Research, 1991
Electrophysiological measurements have shown that contrast adaptation can increase the contrast gain of cortical cells of the cat and the monkey. This implies that adaptation could enhance the contrast discrimination sensitivity. Psychophysical contrast discrimination experiments were performed with and without contrast adaptation.
L M, Määttänen, J J, Koenderink
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Context-specific adaptation of saccade gain

Experimental Brain Research, 2002
Previous studies established that vestibular reflexes can have two adapted states (e.g., gain) simultaneously, and that a context cue (e.g., vertical eye position) can switch between the two states. The present study examined this phenomenon of context-specific adaptationfor horizontal saccades, using a variety of contexts.
Mark, Shelhamer, Richard A, Clendaniel
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Dynamical adaptation in photoreceptors with gain control

Physical Biology, 2022
Abstract The retina hosts all processes needed to convert external visual stimuli into a neural code. Light phototransduction and its conversion into an electrical signal involve biochemical cascades, ionic regulations, and different kinds of coupling, among other relevant processes.
Miguel Castillo García, Eugenio Urdapilleta   +1 more
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Adaptive identification as gain scheduling

Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301), 2002
We consider the Lyapunov approach to adaptive identification for systems with unknown time invariant parameter. We describe the adaptive identification problem as stability analysis for a linear parameter varying system, and then discuss the convergence of identification error and its convergence rate based on a parameter dependent Lyapunov function.
R. Watanabe, K. Uchida
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