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Fast Fourier Transform (FFT) relies on the HRV frequency-domain analysis techniques. It requires re-sampling of the inherently unevenly sampled heartbeat time-series (RR tachogram) to produce an evenly sampled time series of the heartbeat.…

Medical Physics · Physics 2022-08-04 Amin Gasmi

The graph Hilbert transform (GHT) is a key tool in constructing analytic signals and extracting envelope and phase information in graph signal processing. However, its utility is limited by confinement to the graph Fourier domain, a fixed…

Signal Processing · Electrical Eng. & Systems 2025-09-23 Daxiang Li , Zhichao Zhang

Fourier representation (FR) is an indispensable mathematical formulation for modeling and analysis of physical phenomenon, engineering systems and signals in numerous applications. In this study, we present the generalized Fourier…

Signal Processing · Electrical Eng. & Systems 2020-08-28 Pushpendra Singh

The behavior of stock market returns over a period of 1-60 days has been investigated for S&P 500 and Nasdaq within the framework of nonextensive Tsallis statistics. Even for such long terms, the distributions of the returns are…

Statistical Finance · Quantitative Finance 2017-09-18 Sandhya Devi

I discuss the nature of a Fractional Discrete Fourier Transform (FrDFT) described algorithmically by a combination of chirp transforms and ordinary DFTs. The transform is shown to be consistent with a continuous two-dimensional rotation…

General Mathematics · Mathematics 2019-10-01 Evan Zayas

Graph signal processing (GSP) facilitates the analysis of high-dimensional data on non-Euclidean domains by utilizing graph signals defined on graph vertices. In addition to static data, each vertex can provide continuous time-series…

Signal Processing · Electrical Eng. & Systems 2025-02-21 Tuna Alikaşifoğlu , Bünyamin Kartal , Eray Özgünay , Aykut Koç

The Fast Fourier Transform (FFT) is one of the most widely used algorithms in high performance computing, with critical applications in spectral analysis for both signal processing and the numerical solution of partial differential…

Numerical Analysis · Mathematics 2025-05-01 Laslo Hunhold , John Gustafson

The work fluctuation theorem (FT) is a symmetry connecting the moment generating functions (MGFs) of the work extracted in a given process and in its time-reversed counterpart. We show that, equivalently, the FT for work in isolated quantum…

Quantum Physics · Physics 2023-11-29 Vasco Cavina , Sadeq S. Kadijani , Massimiliano Esposito , Thomas Schmidt

In this paper, we study the problems in the discrete Fourier transform (DFT) test included in NIST SP 800-22 released by the National Institute of Standards and Technology (NIST), which is a collection of tests for evaluating both physical…

Cryptography and Security · Computer Science 2018-03-08 Hiroki Okada , Ken Umeno

The graph fractional Fourier transform (GFRFT) for unitary graph Fourier transform (GFT) matrices can be interpreted through the scalar function $e^{j\alpha\theta}$ on the unit circle. Under the principal branch, its Fourier-series…

Signal Processing · Electrical Eng. & Systems 2026-05-19 Ziqi Yan , Mingzhi Wang , Sen Shi , Feiyue Zhao , Manjun Cui , Yangfan He , Zhichao Zhang

The FFT algorithm that implements the discrete Fourier transform is considered one of the top ten algorithms of the $20$th century. Its main strengths are the low computational cost of $\mathcal{O}(n \log n$) and its stability. It is one of…

Numerical Analysis · Mathematics 2017-06-15 Matteo Briani , Annie Cuyt , Wen-shin Lee

We develop the basic building blocks of a frequency domain framework for drawing statistical inferences on the second-order structure of a stationary sequence of functional data. The key element in such a context is the spectral density…

Statistics Theory · Mathematics 2013-05-10 Victor M. Panaretos , Shahin Tavakoli

The low-T part of the phase diagram in self-assembling systems is correctly predicted by the known versions of the density functional theory (DFT). The high-T part obtained in DFT, however, does not agree with simulations even on the…

Soft Condensed Matter · Physics 2018-11-20 A. Ciach

We argue that negative skew and positive mean of the distribution of stock returns are largely due to the broken symmetry of stochastic volatility governing gains and losses. Starting with stochastic differential equations for stock returns…

Statistical Finance · Quantitative Finance 2026-03-10 Siqi Shao , Arshia Ghasemi , Hamed Farahani , R. A. Serota

We study the Fluctuation Theorem (FT) for entropy production in chaotic discrete-time dynamical systems on compact metric spaces, and extend it to empirical measures, all continuous potentials, and all weak Gibbs states. In particular, we…

Mathematical Physics · Physics 2026-02-13 Noé Cuneo , Vojkan Jakšić , Claude-Alain Pillet , Armen Shirikyan

This paper proposes regenerative particle Thompson sampling (RPTS), a flexible variation of Thompson sampling. Thompson sampling itself is a Bayesian heuristic for solving stochastic bandit problems, but it is hard to implement in practice…

Machine Learning · Computer Science 2024-01-24 Zeyu Zhou , Bruce Hajek , Nakjung Choi , Anwar Walid

We propose a nonparametric estimator of the empirical distribution function (EDF) of the latent spot variance of the log-price of a financial asset. We show that over a fixed time span our realized EDF (or REDF) -- inferred from noisy…

Econometrics · Economics 2026-01-29 Kim Christensen , Martin Thyrsgaard , Bezirgen Veliyev

We extend our recently developed sparse-stochastic fragmented exchange formalism for ground-state hybrid DFT (ngH-DFT) to calculate absorption spectra within linear-response time-dependent Generalized Kohn-Sham DFT (LR-GKS-TDDFT), for…

Chemical Physics · Physics 2025-03-11 Mykola Sereda , Tucker Allen , Nadine C. Bradbury , Khaled Z. Ibrahim , Daniel Neuhauser

Based on the cryptocurrency market dynamics, this study presents a general methodology for analyzing evolving correlation structures in complex systems using the $q$-dependent detrended cross-correlation coefficient \rho(q,s). By extending…

Statistical Finance · Quantitative Finance 2025-10-29 Marcin Wątorek , Marija Bezbradica , Martin Crane , Jarosław Kwapień , Stanisław Drożdż

The Random Variable Transformation (RVT) method is a fundamental tool for determining the probability distribution function associated with a Random Variable (RV) Y=g(X), where X is a RV and g is a suitable transformation. In the usual…

Probability · Mathematics 2024-05-07 Fabrizio Masullo , Fabio Zanolin , Josep Bonet Avalos
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