IEEE

Convergence Theorems for Stochastic Impulsive Systems With Application to Discrete-Time Stochastic Feedback Control

Abstract: This article is devoted to stochastic convergence theorems for stochastic impulsive systems (SISs) and their application to discrete-time stochastic feedback control (DTSFC). A general ...
Tech Xplore

Discrete spatial diffusion models data while obeying scientific principles

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI ...
GitHub

Is Mamba Effective for Time Series Forecasting?

We propose S-Mamba, a Mamba-based model for time series forecasting, which delegates the extraction of inter-variate correlations and temporal dependencies to a bidirectional Mamba block and a ...
Scientific Research Publishing

Inflation Co-Movement Dynamics in SADC: A Continuous Wavelet Analysis ()

This study examines the co-movement dynamics of inflation rates among Southern African Development Community (SADC) member ...

Understanding Fourier Analysis: Uncovering Patterns in Time Series Data

Discover how Fourier Analysis breaks down complex time series data into simpler components to identify trends and patterns, despite its limitations in stock forecasting.
GitHub

Time Series Foundation Model - TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting

The official code for ["TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting (ICLR 2024)"]. TEMPO is one of the very first open source Time Series Foundation Models for ...
IEEE

Arbitrary Modulation of Average Dwell Time in Discrete-Time Markov Chains Based on Tunneling Magnetoresistance Effect

Abstract: Stochastic processes (SPs) are widely used in many real-world fields, especially AI algorithms and models. A discrete-time Markov chain (DTMC) is a fundamental SP where the probability of ...