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What is the state space?

Composite number

Elasticity (physics)

Finite element method

Composite laminates

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The state space refers to a modeling framework used in various fields like composite laminates analysis, time series modeling, and quantitative ecology. In composite laminates, the state space theory (SST) is a method that does not assume displacement or stress along the thickness direction, providing an accurate advantage for displacement and stress analysis. In time series modeling, state-space models describe the dynamics of a system over time and link observed data with the true underlying state, offering flexibility and simplifying model specification. In quantitative ecology, state-space models are crucial for analyzing time-series data, capturing the different processes within a complex system and aiding in model fitting with varying complexities.

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Peer Review•DOI State‐space models for ecological time‐series data: Practical model‐fitting Ken B. Newman, Ruth King, Victor Elvira, Perry de Valpine, Rachel S. McCrea, Byron J. T. Morgan - Show less +5 more 21 Feb 2022-Methods in Ecology and Evolution 8 Citations	The state space in ecological time-series data refers to the dynamics of the true underlying state of the system over time, encompassing system and observation processes within state-space models.
Open access•Posted Content•DOI Graph state-space models 04 Jan 2023	The state space in graph state-space models refers to maintaining a system's updated representation for making predictions, incorporating relational information learned from spatio-temporal data to enhance modeling effectiveness.
Open access•Journal Article•DOI State‐space models for ecological time‐series data: Practical model‐fitting Yuno INOUE 30 Mar 2022-Methods in Ecology and Evolution 5 Citations	The state space in ecological time-series data refers to the system and observation processes that describe the dynamics of the true underlying state of the system over time.
Journal Article•DOI Graph state-space models Daniele Zambon, Andrea Marie Cini, Lorenzo Livi, Cesare Alippi - Show less +3 more 04 Jan 2023-arXiv.org 1 Citations	The state space in the context of the paper refers to a modeling framework that captures latent dependencies among signals in spatio-temporal data for effective forecasting within a probabilistic formulation.
Book Chapter•DOI State space theory Belem Marisol Uribe Alcántara 01 Jan 2022	State space theory (SST) is a specialized analysis method for composite laminates, incorporating displacement and stress without assumptions along the thickness direction, offering accurate solutions for composite structures.

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What are the latest papers on state space model?5 answersState space models (SSMs) have recently shown promising results in sequence and language modelling tasks, outperforming attention-based approaches. One paper proposes a multi-head state space (MH-SSM) architecture with special gating mechanisms, achieving state-of-the-art performance on the LibriSpeech speech recognition task. Another paper explores the use of SSMs for counterfactual outcome prediction in longitudinal data, comparing two models: Treatment Effect Neural Controlled Differential Equation (TE-CDE) and structured state space model (S4Model). S4Model outperforms TE-CDE in terms of training time, normalized mean squared error, stability, and sensitivity to weight initialization. Additionally, a paper presents a small signal analytical state-space model for a Full Bridge MMC converter, demonstrating good accuracy and improved damping of oscillatory modes. Lastly, a paper proposes a state-space approach to estimate potential growth and natural interest rates, considering financial variables as determinants of the business cycle.

What are the computer vision papers published after 2022 using state space model?5 answersComputer vision papers published after 2022 using state space models include a nonparametric method for identification of MIMO linear parameter-varying (LPV) models in state-space form. Another paper discusses the use of computer vision in various fields such as industry, medicine, zoology, and social life, with the ResNet neural network model being the most popular method. Additionally, a conference brings together practitioners and researchers in intelligent robots and computer vision, focusing on topics such as imaging sensors, machine vision technology in different industries, and sensor fusion for intelligent robotics. Furthermore, a new framework called graphical state space model is proposed for real-time optimal estimation of nonlinear state space models, outperforming the Extended Kalman filter in some cases. Lastly, a paper presents a new approach to estimate unstable flame dynamics using computer vision processed images and Operational Modal Analysis, providing a tool for improving control strategies in industrial oil furnaces.

What is the meaning of state transformation?5 answersState transformation refers to the changes that occur in the structure and functioning of states in response to various factors such as globalization, neoliberalism, and the emergence of heterarchy. These changes involve the reconfiguration of national states to adapt to new economic and political dynamics, as well as the decentralization and internationalization of state apparatuses. State transformation is a necessary precondition for the emergence of heterarchy and the retheorization of world politics. However, it is important to note that states still retain important powers and capacities, and they are being reconfigured in ways that suit dominant social forces. State transformation is a complex process that involves the empowerment of technocratic experts and the embedding of global governance agendas within domestic governance processes. It is also influenced by socio-political contestation and the legitimacy of governance regimes.

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