Abstract: DC-DC converters are extensively deployed across a range of new energy applications. However, traditional control methods that rely on accurate state space models encounter limitations in dc ...
For visual generation, discrete autoregressive models often struggle with poor tokenizer reconstruction, difficulties in sampling from large vocabularies, and slow token-by-token generation speeds. We ...
This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...
Discover how to build a homemade rubber band-powered paper airplane in this easy and engaging tutorial. We’ll guide you step-by-step as you craft the frame with skewers, add aerodynamic paper wings, ...
Abstract: System identification is essential for modeling and control of nonlinear dynamic systems. In practice, traditional linear or unidirectional recurrent models often fail to capture the ...
ABSTRACT: This study investigates the relationship between public debt and economic growth in Uganda for the period 1990 to 2023 using a nonlinear autoregressive distributed lag (NARDL) model. The ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...
Chaotic systems, such as fluid dynamics or brain activity, are highly sensitive to initial conditions, making long-term predictions difficult. Even minor errors in modeling these systems can rapidly ...
ABSTRACT: This paper aims to study the GARCH-X model based on high-frequency data. Building upon the existing research on the selection criteria for optimal volatility representation and parameter ...
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