Results 71 to 80 of about 9,100,775 (301)
On Certain Matrices of Bernoulli Numbers [PDF]
Abstract and Applied Analysis, 2014 In this work we compute the determinant and inverse matrices for a certain symmetric matrix of Rayleigh sums. As a special case we also obtain the determinants and inverses for the matrices of the Bernoulli numbers and related numbers.
Zhang, Ruiming, Chen, Li-Chen
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Device Stochasticity Directly Implements Bayesian Sampling in Spiking Neurons
Advanced Science, EarlyView.Brain‐inspired stochastic spiking turns device noise into Bayesian uncertainty for robust, low‐power neuromorphic computing. ABSTRACT Device stochasticity is considered a non‐ideality in neuromorphic hardware, although stochastic neural activity supports probabilistic computation in biological systems.
Huannan Zheng, Jingli Liu, Kezhou Yang
wiley +1 more source
Euler's constant, sequences and some estimates [PDF]
Surveys in Mathematics and its Applications, 2013 We give a class of sequences with the argument of the logarithmic term modified and that converge quickly to a generalization of Euler's constant denoted by γ(a), i.e. the limit of the sequence (∑k=1n1/(a+k-1)-ln((a+n-1)/a)n∈ℕ, where a∈(0,+∞).
Alina Sîntămărian
doaj
q-Bernoulli numbers and polynomials
Duke Mathematical Journal, 1948 Verf. definiert die \(q\)-Bernoullischen Zahlen \(\beta_m\) durch \(\beta_0=1\), \(\beta_1=-1/(q+1)\) und die symboli\-sche Rekursionsformel \(q(q\beta+1)^m=0\) \((m>1)\), wobei \(\beta^i\) nach Entwicklung durch \(\beta_i\) zu ersetzen ist. Die Zahlen \(\beta_m\) stimmen für \(q=1\) mit den gewöhnlichen Bernoullischen Zahlen überein.
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A Note on Bernoulli Numbers and Shintani Generalized Bernoulli Polynomials [PDF]
Transactions of the American Mathematical Society, 1996 Generalized Bernoulli polynomials were introduced by Shintani in 1976 in order to express the special values at non-positive integers of Dedekind zeta functions for totally real numbers. The coefficients of such polynomials are finite combinations of products of Bernoulli numbers which are difficult to get hold of.
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ReLink: Reliable Deep Learning for Microscopic Motion Tracking
Advanced Science, EarlyView.ReLink enables reliable trajectory linking in single‐particle tracking by integrating physics‐informed motion statistics with confidence‐based adaptive filtering. Across diverse simulated and experimental conditions, ReLink robustly reconstructs trajectories and preserves the fidelity of downstream analyses, enabling accurate characterization of ...
Yuan Jiang +7 more
wiley +1 more source
Advanced Science, EarlyView.This study reports a knot‐shaped single‐capillary open microfluidic probe (Knot‐probe) for robust and versatile spatial omics, enabling ambient mass spectrometry imaging with high spatial resolution, throughput, and structure‐resolved capability. Knot‐probe mitigates the trade‐off between analytical performance and operational robustness, providing an ...
Xiangyu Zhu +10 more
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Blind deconvolution of sparse pulse sequences under a minimum distance constraint: a partially collapsed Gibbs sampler method [PDF]
, 2012 For blind deconvolution of an unknown sparse sequence convolved with an unknown pulse, a powerful Bayesian method employs the Gibbs sampler in combination with a Bernoulli–Gaussian prior modeling sparsity.
Kail, Georg +3 more
core +1 more source
Cubic harmonics and Bernoulli numbers
Journal of Combinatorial Theory, Series A, 2012 18 pages, 3 ...
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Stochastic‐MTJ Sampler Arrays for In‐Array Monte–Carlo Estimation
Advanced Electronic Materials, EarlyView.A low‐energy‐barrier magnetic tunnel junction array is operated as a probability‐domain sampler: each cell's random switching, programmed through a shared digital‐to‐analog converter, makes the per‐column multiply–accumulate an unbiased Monte–Carlo expectation estimator that returns both a mean and a calibrated uncertainty.
Ran Zhang +6 more
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