Abstract:- This paper is motivated by the fact that though weighted component based non-linear model approximation techniques are popular engineering tools, their utilisation is being restricted by their exponential complexity caused by the number of components. Even i ca e when the components are generated by some expert operator, the approximations usually have redundant or weakly contributing components resulting in exponentially growing unnecessary calculation. The main objective of this paper is to propose a complexity reduction technique capable of finding the minimal number of components of a given approximation. Key-Words:- Model approximation, model reduction, calculation complexity, singular value decomposition
Although faster computers have been developed in recent years, they tend to be used to solve even mo...
We compare the cost complexities of two approximation schemes for functions that live on the product...
An increasing complexity of models used to predict real-world systems leads to the need for algorith...
In this thesis a number of problems from model reduction and approximation in systems and control th...
Mathematical models are obtained from first principles (natural laws, interconnec-tion, etc.) and ex...
AbstractThe operation of multiplication of a vector by a matrix can be represented by a computationa...
The operation ‘multiplication of a vector by a matrix ’ can be represented by a computational scheme...
In order to approximate multidimensional function it is necessary to select the complexity of the mo...
In this paper a new frequency weighted partial fraction expansion based model reduction technique is...
International audienceModels encountered in chemical engineering usually involve a large number of d...
We consider the problem of efficiently computing models for satisfiable constraints, in the presence...
Modelling and simulation nowadays permeate virtually any engineering activity, requiring tools capab...
Large complex mathematical models are regularly used for simulation and prediction. However, in cont...
Model reduction techniques are often required in computationally tractable algorithms for the soluti...
[[abstract]]This paper proposes a simple method of model reduction for discrete multivariable system...
Although faster computers have been developed in recent years, they tend to be used to solve even mo...
We compare the cost complexities of two approximation schemes for functions that live on the product...
An increasing complexity of models used to predict real-world systems leads to the need for algorith...
In this thesis a number of problems from model reduction and approximation in systems and control th...
Mathematical models are obtained from first principles (natural laws, interconnec-tion, etc.) and ex...
AbstractThe operation of multiplication of a vector by a matrix can be represented by a computationa...
The operation ‘multiplication of a vector by a matrix ’ can be represented by a computational scheme...
In order to approximate multidimensional function it is necessary to select the complexity of the mo...
In this paper a new frequency weighted partial fraction expansion based model reduction technique is...
International audienceModels encountered in chemical engineering usually involve a large number of d...
We consider the problem of efficiently computing models for satisfiable constraints, in the presence...
Modelling and simulation nowadays permeate virtually any engineering activity, requiring tools capab...
Large complex mathematical models are regularly used for simulation and prediction. However, in cont...
Model reduction techniques are often required in computationally tractable algorithms for the soluti...
[[abstract]]This paper proposes a simple method of model reduction for discrete multivariable system...
Although faster computers have been developed in recent years, they tend to be used to solve even mo...
We compare the cost complexities of two approximation schemes for functions that live on the product...
An increasing complexity of models used to predict real-world systems leads to the need for algorith...