Results 21 to 30 of about 4,258,467 (384)

Discrete Information Dynamics with Confidence via the Computational Mechanics Bootstrap: Confidence Sets and Significance Tests for Information-Dynamic Measures

open access: yesEntropy, 2020
Information dynamics and computational mechanics provide a suite of measures for assessing the information- and computation-theoretic properties of complex systems in the absence of mechanistic models.
David Darmon
doaj   +1 more source

Counting curves via lattice paths in polygons [PDF]

open access: yes, 2003
This note presents a formula for the enumerative invariants of arbitrary genus in toric surfaces. The formula computes the number of curves of a given genus through a collection of generic points in the surface.
Mikhalkin, Grigory
core   +7 more sources

A Computational Systems Pharmacology Approach to Investigate Molecular Mechanisms of Herbal Formula Tian-Ma-Gou-Teng-Yin for Treatment of Alzheimer’s Disease

open access: yesFrontiers in Pharmacology, 2018
Traditional Chinese medicine (TCM) is typically prescribed as formula to treat certain symptoms. A TCM formula contains hundreds of chemical components, which makes it complicated to elucidate the molecular mechanisms of TCM.
Tianduanyi Wang   +5 more
semanticscholar   +1 more source

On computing Gauss-Kronrod quadrature formulae [PDF]

open access: yesMathematics of Computation, 1986
We discuss the use of Newton’s method for computing Gauss-Kronrod quadrature formulae from modified moments. The underlying nonlinear maps are analyzed from the point of view of numerical condition. A method is indicated of computing the polynomial whose zeros are the Kronrod nodes.
CALIO', FRANCA   +2 more
openaire   +2 more sources

Accelerating Spike-by-Spike Neural Networks on FPGA With Hybrid Custom Floating-Point and Logarithmic Dot-Product Approximation

open access: yesIEEE Access, 2021
Spiking neural networks (SNNs) represent a promising alternative to conventional neural networks. In particular, the so-called Spike-by-Spike (SbS) neural networks provide exceptional noise robustness and reduced complexity.
Yarib Nevarez   +3 more
doaj   +1 more source

Asymptotic unbounded root loci - Formulae and computation [PDF]

open access: yes1981 20th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes, 1981
We study the asymptotic behavior of the dosed loop eigenvalues (root loci) of a strictly proper linear time-invariant control system as loop gain goes to \infty . The formulas are stated in terms of the eigenvalues of nested restricted linear maps of the form A(\mod S_{2})|_{S_{1}} where S 1 and S 2 are subspaces of complementary dimension.
Sastry, S. Shankar, Desoer, Charles A.
openaire   +1 more source

Analysis and Implementation of Robust Metaheuristic Algorithm to Extract Essential Parameters of Solar Cell

open access: yesIEEE Access, 2022
Optimization complications are solved using meta-heuristic methods, which transforms the complex data into simplest way and computational process is quite attractive because of their intensification, diversification, and accurate evaluating/computational
Sairaj Arandhakar   +4 more
doaj   +1 more source

One kind sixth power mean of the three-term exponential sums

open access: yesOpen Mathematics, 2017
In this paper, we use the estimate for trigonometric sums and the properties of the congruence equations to study the computational problem of one kind sixth power mean of the three-term exponential sums.
Wang Xiaoying, Li Xiaoxue
doaj   +1 more source

On the High-Power Mean of the Generalized Gauss Sums and Kloosterman Sums

open access: yesMathematics, 2019
The main aim of this paper is to use the properties of the trigonometric sums and character sums, and the number of the solutions of several symmetry congruence equations to research the computational problem of a certain sixth power mean of the ...
Xinyu Liu, Wenpeng Zhang
doaj   +1 more source

An Inverse-Free and Scalable Sparse Bayesian Extreme Learning Machine for Classification Problems

open access: yesIEEE Access, 2021
Sparse Bayesian Extreme Learning Machine (SBELM) constructs an extremely sparse and probabilistic model with low computational cost and high generalization.
Jiahua Luo   +3 more
doaj   +1 more source

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