Results 241 to 250 of about 90,056 (287)

Propagation properties of a non-linear mapping based on squaring in odd characteristic. [PDF]

Cryptogr Commun
Daemen J, Kuijsters D, Mella S, Verbakel D.   +3 more
europepmc   +1 more source

Inference on spatiotemporal dynamics for coupled biological populations. [PDF]

J R Soc Interface
Li J, Ionides EL, King AA, Pascual M, Ning N.   +4 more
europepmc   +1 more source

Multi-Sensor Fusion for Wheel-Inertial-Visual Systems Using a Fuzzification-Assisted Iterated Error State Kalman Filter. [PDF]

Sensors (Basel)
Huang G, Huang H, Zhai Y, Tang G, Zhang L, Gao X, Huang Y, Ge G.   +7 more
europepmc   +1 more source

Iterative variational learning of committor-consistent transition pathways using artificial neural networks. [PDF]

Nat Comput Sci
Megías A, Contreras Arredondo S, Chen CG, Tang C, Roux B, Chipot C.   +5 more
europepmc   +1 more source

Behavioral Time Scale Synaptic Plasticity (BTSP) endows binding of distributed representations with flexible retrieval options

Yu C, Yang Y, Wu Y, Wang A, Maass W.
europepmc   +1 more source

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On the progressive iteration approximation property and alternative iterations

Computer Aided Geometric Design, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jesús M. Carnicer, Jorge Delgado 0001, Juan Manuel Peña 0001   +2 more
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Iterated approximate value functions

2013 European Control Conference (ECC), 2013
In this paper we introduce a control policy which we refer to as the iterated approximate value function policy. The generation of this policy requires two stages, the first one carried out off-line, and the second stage carried out on-line. In the first stage we simultaneously compute a trajectory of moments of the state and action and a sequence of ...
Brendan O'Donoghue, Yang Wang 0021, Stephen P. Boyd   +2 more
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Classification-Based Approximate Policy Iteration

IEEE Transactions on Automatic Control, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Amir-massoud Farahmand, Doina Precup, André da Motta Salles Barreto, Mohammad Ghavamzadeh   +3 more
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Approximation and Iteration

1970
For practical purposes, it is often necessary to work out a good estimate of the value of a function f: I ↔ ℝ at each x ∈ I. One method is to use the Taylor expansion with integral form of the remainder, as follows. Let I = ⩾p, q⩽ suppose f ∈ 𝒞n + 1 (I) (see 29.6), and 0 ∈ .
H. B. Griffiths, P. J. Hilton
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