state-space model representation
Continuous state-space representation of a bucket-type rainfall-runoff model: a case study with the GR4 model using state-space GR4 (version 1.0)
... rainfall–runoff model explicit and to solve them continu- ...comprehensive state-space representation of the ...the model more complex, could be removed. In this state- ...
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Use of Extended Kalman Filter in Estimation of Attitude of a Nano-Satellite
... — State estimation theory is one of the best mathematical approaches to analyze the changes in the states of a system or a ...The state of the system is defined by a set of variables that provide a complete ...
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II.T HE DYNAMIC MODEL OF BLDC MOTOR SYSTEM A. State-space representation of BLDC motor system
... a model of a particular commercial BLDC motor derived through standard system identification demonstrated the applicability and robustness of the proposed control technique to changes to internal BLDC resistance ...
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A Reference Dependent Representation with Subjective Tastes
... state space, where each state is identi…ed with an ex post subjective ...post state utilities to be of the expected utility ...subjective state space characteristic to the Kreps ...
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Reliability state space model of Power Transformer
... In general, a bathtub curve may be used as an adequate representation of a transformer failure mode with varying life time[14]. Accelerated life testing has shown that transformer have a bathtub curved failure ...
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A Flexible State Space Model and its Applications
... the model structure implied by the standard ...flexible model allows dynamic dimensions of the state and measurement vectors, lagged observations in the equations and first-lagged state vector ...
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Generalized Estimation of Missing Observations in Nonlinear Time Series Model Using State Space Representation
... Most methods developed for estimation of missing ob- servations in time series Analysis, have been limited to the case of one or two consecutive missing observations. In this paper, we have employed the state ...
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Application of Self-Tuning Control System for Solution of Fault Tolerance Problem
... order model should also be of the Hankel ...time state space realisation of the process can be determined from the relationship between Markov parameters and representation of the Hankel ...
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A Survey of Quantum Theory Inspired Approaches to Information Retrieval
... sample space, QT represents events as subspaces of an abstract, complex vector space (called Hilbert space) [Busemeyer and Bruza ...Hilbert space. This method of representation can help ...
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A Learning State-Space Model for Image Retrieval
... tasks: representation and estimation for the ...the state, which intuitively handles the semantic gap between vi- sual features and user ...semantic space for image retrieval because it is impossible ...
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The State of the Art in Semantic Representation
... Vector Space Models (VSM), which eschew the use of symbolic structures, instead modeling all linguis- tic elements as vectors, from the level of words to phrases and ...to model non-local and gradient ...
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Safe Multi-objective Planning with a Posteriori Preferences
... POMDP state search space) of the model representation – we can update the process model approximately when running expensive simulations in our planning algorithm, whereas the safety ...
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State space models: Univariate representation of a multivariate model, partial interpolation and periodic convergence
... the model for LBB, chosen according to the selection criteria recommended by DeGaetano et a l (1995), were ABI (Abilene, TX), AMA (Amarillo, TX) and MAF (Midland, ...
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Identification of speculative bubbles using state-space models with Markov-switching
... stock-price model. In the state-space representation of this model, the unobservable state vector constitutes the bubble component and by allowing the bubble process to switch ...
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Model Predictive Control Structures in Non Minimal State Space
... This chapter presents a NMSS/MPC formulation for systems with a modelled measured disturbance. Modelled disturbances can be any measurable but un controllable s}fstem inputs th a t affect the system state or ...
204
Forecasting macroeconomic variables using a structural state space model
... The three key advantages 2 of the state space approach when compared to the (vec- tor) ARMA alternative are generality, flexibility, and transparency. For example, as shown in this paper, it generalises ...
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Online State Space Model Parameter Estimation in Synchronous Machines
... In this paper, the theoretical relation based approach, which uses the known least square error method, has been presented to identify the nonlinear 3 rd order synchronous generator state space model ...
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Linear system identification of longitudinal vehicle dynamics versus nonlinear physical modelling
... Given that firstly, linear feedback control schemes are rela- tively tolerant of plant model error (e.g. due to nonlinearities), and secondly, nonlinearities in vehicles are relatively weak (although become ...
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INTEGRATING ANALYTICAL AEROELASTIC INSTABILITY ANALYSIS INTO DESIGN OPTIMIZATION OF AIRCRAFT WING STRUCTURES
... CAD model constructed in CATIA V5 by Nikbay [14] and also determined from the known geometrical properties of the standart ...weakened model for natural frequency determination and experimental results for ...
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A Gaussian Mixture Approach to Blind Equalization of Block-Oriented Wireless Communications
... continuous state-space representation of the communication system, we introduce a blind Bayesian equalization algorithm based on a Gaussian mixture parameterization of the a posteriori probability ...
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