搜索结果: 1-15 共查到“State space”相关记录30条 . 查询时间(0.12 秒)
Using State Space Encoding To Counter Biased Fault Attacks on AES Countermeasures
Cryptanalysis Time Redundancy Biased Faults
2015/12/24
Biased fault attacks such as the Differential Fault
Intensity Analysis (DFIA) have been a major threat to cryptosystems
in recent times. DFIA combines principles of side
channel analysis and fault ...
Optimal Synthesis and Explicit State-Space Solution for a Decentralized Two-Player Linear-Quadratic Regulator
Two-Player Linear-Quadratic State-Space Solution
2015/6/19
In this paper, we develop controller synthesis algorithms for decentralized control problems. The system considered here is an information structure, consisting of two interconnected linear subsystems...
An Explicit State-Space Solution for a Decentralized Two-Player Optimal Linear-Quadratic Regulator
Two-Player State-Space Solution
2015/6/19
We develop controller synthesis algorithms for decentralized control problems, where individual subsystems are connected over a network. We focus on the simplest information structure, consisting of t...
A State-Space Solution to the Two-Player Decentralized Optimal Control Problem
Optimal Control Problem Two-Player Decentralized
2015/6/19
In this paper, we present an explicit state-space solution to the two-player decentralized optimal control problem. In this problem, there are two interconnected linear systems that seek to optimize a...
武汉理工大学轮机仿真及控制技术英文课件Lecture5 State-space modeling and control of ship propulsion
武汉理工大学 轮机仿真及控制技术 英文 课件 Lecture5 State-space modeling and control of ship propulsion
2015/6/1
武汉理工大学轮机仿真及控制技术英文课件Lecture5 State-space modeling and control of ship propulsion。
山东理工大学现代控制理论课件Chapter 2 State Space Description of Linear Control System
山东理工大学现 现代控制理论 课件 Chapter 2 State Space Description of Linear Control System
2014/7/21
山东理工大学现代控制理论课件Chapter 2 State Space Description of Linear Control System。
MCMC for non-linear state space models using ensembles of latent sequences
MCMC non-linear state space models ensembles latent sequences
2013/6/13
Non-linear state space models are a widely-used class of models for biological, economic, and physical processes. Fitting these models to observed data is a difficult inference problem that has no str...
Propagation of initial errors on the parameters for linear and Gaussian state space models
Kalman filter Extended Kalman filter State space mod-els Autoregressive process
2013/4/27
For linear and Gaussian state space models parametrized by $\theta_0 \in \Theta \subset \R^{r}, r \geq 1$ corresponding to the vector of parameters of the model, the Kalman filter gives exactly the so...
State-space solutions to the dynamic magnetoencephalography inverse problem using high performance computing
Magnetoencephalography source localization Kalman filter fixed interval smoother
2011/8/17
Abstract: Determining the magnitude and location of neural sources within the brain that are responsible for generating magnetoencephalography (MEG) signals measured on the surface of the head is a ch...
Canonical lossless state-space systems: Staircase forms and the Schur algorithm
Lossless systems input normal forms output normal forms balanced canonical forms
2011/2/21
A new finite atlas of overlapping balanced canonical forms for multivariate discrete-time lossless systems is presented. The canonical forms have the property that the controllability matrix is positi...
Research on the state space reconstruction applying in fault diagnosis of Diesel engine
State space reconstruction Phase Diagram Analysis
2010/9/25
Analyzing the data of diesel surface vibration acceleration monitoring, the method of state space reconstruction was applied. Processing the vibration acceleration signal via integration and filtering...
Non-asymptotic deviation inequalities for smoothed additive functionals in non-linear state-space models with applications to parameter estimation
Non-asymptotic deviation inequalities smoothed additive functionals in non-linear state-space parameter estimation
2011/2/22
Approximating joint smoothing distributions using particle-based methods is a well-known issue in statistical inference when operating on general state space hidden Markov models (HMM). In this paper ...
Convex Optimization In Identification Of Stable Non-Linear State Space Models
Convex Optimization Identification Stable Non-Linear State Space Models
2010/12/1
A new framework for nonlinear system identification is presented in terms of optimal fitting of stable nonlinear state space equations to input/output/state data, with a performance objective defined ...
Counting SO(9)xSU(2) representations in coordinate independent state space of SU(2) Matrix Theory
Counting SO(9)xSU(2) representations SU(2) Matrix Theory
2010/12/8
We consider decomposition of coordinate independent states into SO(9)×SU(2)representations in SU(2) Matrix theory. To see what and how many representations appear in the decomposition, we compute the ...
Configuration Selection for Reconfigurable Manufacturing Systems by Means of Characteristic State Space
reconfigurable manufacturing system configuration selection
2011/8/3
The configuration selection for reconfigurable manufacturing systems(RMS) have been tackled in a number of studies by using analytical or simulation models. The simulation models are usually based on ...