The simulation of stationary time-series (discrete-time random process) with a specific autocorrelation function (ACF) and continuous probability distribution.
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- Python
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random-process
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A comprehensive toolkit for ergodicity economics and related fields.
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- Python
CS 5291 Stochastic Process for Networking 2022 Course Materials
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This repository consists of codes that I developed for EEG and ECG signal processing
eeg ecg filter-design eeg-analysis non-stationary ecg-signal-python ecg-filtering eeg-classification autoregressive-processes ecg-analyzer band-pass-filter random-process
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- MATLAB
Matlab code to generate atmospheric turbulence for skew flow. Application: Wind engineering, structural dynamics, boundary layer meteorology.
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- MATLAB
Minimalist Matlab implementation of a random process generation in one point
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- MATLAB
Analyzing random processes to determine stationarity using statistical methods and implements analog-to-digital conversion, quantization, and signal transmission with noise in MATLAB.
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- MATLAB
Contains several MATLAB codes to run forward UQ using intrusive (stochastic Galerkin finite element method) or non-intrusive (sampling/quadrature), Karhunen-Loeve expansion etc.
matlab quadrature uncertainty-quantification stochastic-processes random-process non-intrusive random-variable stochastic-galerkin-fem
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- MATLAB
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- Python
Matlab functions to test the stationarity of a random process
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- MATLAB
A non-Gaussian distribution is generated from a Gaussian-distributed white noise
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- MATLAB
Some statistical method in diffusion stochastic processes. Numerical schemes and parameter estimation
finance parameter-estimation quantitative-finance numerical-methods stochastic-processes random-process
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- Jupyter Notebook
Practical implementation of algorithms, concepts and techniques from subjects such as Linear Algebra, Random Processes & Probability and PyTorch.
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- Jupyter Notebook
Markov Analysis using Rust
probability markov-chain text-generation random-generation markov-text stochastic-processes random-process
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- Rust
Apuntes sobre el libro "Probability, random variables, and stochastic processes" de Athanasios Papoulis y S. Unnikrishna Pillai.
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- TeX
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