Results 21 to 30 of about 695,468 (282)
On the convergence of Steffensen-type methods using recurrent functions nonexpansive mappings
We introduce the new idea of recurrent functions to provide a new semilocal convergence analysis for Steffensen-type methods (STM) in a Banach space setting.
Ioannis K. Argyros, Saïd Hilout
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Dose response severity functions for acoustic disturbance in cetaceans using recurrent event survival analysis [PDF]
This work was financially supported by the U. S. Office of Naval Research grant N00014‐12‐1‐0204, under the project “Multi‐study Ocean acoustics Human effects Analysis” (MOCHA). . L.
De Ruiter, Stacy Lynn +7 more
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Semilocal convergence conditions for the secant method, using recurrent functions
Using our new concept of recurrent functions, we present new sufficient convergence conditions for the secant method to a locally unique solution of a nonlinear equation in a Banach space.
Ioannis K. Argyros, Saïd Hilout
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General Recurrent Neural Network for Solving Generalized Linear Matrix Equation
This brief proposes a general framework of the nonlinear recurrent neural network for solving online the generalized linear matrix equation (GLME) with global convergence property. If the linear activation function is utilized, the neural state matrix of
Zhan Li, Hong Cheng, Hongliang Guo
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On Newton's method using recurrent functions under hypotheses up to the second Fréchet derivative
We provide semilocal result for the convergence of Newton method to a locally unique solution of an equation in a Banach space setting using hypotheses up to the second Fréchet-derivatives and our new idea of recurrent functions.
Ioannis K. Argyros, Saïd Hilout
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Despite recent successes in Reinforcement Learning, value-based methods often suffer from high variance hindering performance. In this paper, we illustrate this in a continuous control setting where state of the art methods perform poorly whenever sensor noise is introduced.
Thodoroff, Pierre +4 more
openaire +2 more sources
Many sequential processing tasks require complex nonlinear transition functions from one step to the next. However, recurrent neural networks with 'deep' transition functions remain difficult to train, even when using Long Short-Term Memory (LSTM ...
Koutník, Jan +3 more
core +1 more source
Extinction and recurrence of multi-group SEIR epidemic [PDF]
In this paper, we consider a class of multi-group SEIR epidemic models with stochastic perturbations. By the method of stochastic Lyapunov functions, we study their asymptotic behavior in terms of the intensity of the stochastic perturbations and the ...
Anderson +55 more
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Echo State Condition at the Critical Point
Recurrent networks with transfer functions that fulfill the Lipschitz continuity with K=1 may be echo state networks if certain limitations on the recurrent connectivity are applied.
Mayer, Norbert Michael
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Pathogenetic bases and efficacy of slow calcium channel blockers in the therapy of recurrent peptic ulcer disease associated with hypertension [PDF]
Aim. To clarify blood calcium concentrations (BCCs) as an indicator of the functional state of the calcium-regulating system in the concomitant course of recurrent peptic ulcer disease (PUD) and hypertension, by comparing with the severity of a ulcerous ...
L A Fomina, V V Chernin
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