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This paper addresses the problem of robust identification of a class of discrete-time affine hybrid systems, switched affine models, in a set membership framework. Given a finite collection of noisy input/output data and a bound on the number of subsystems, the objective is to identify a suitable set of affine models along with a switching sequence that can explain the available experimental information...
This paper gives a new procedure for robustness analysis of linear time-invariant (LTI) systems whose state space coefficient matrices depend polynomially on multivariate uncertain parameters. By means of dual linear matrix inequalities (LMIs) that characterize performance of certain LTI systems, we firstly reduce these analysis problems into polynomial matrix inequality (PMI) problems. However, these...
For several decades Grobner bases have proved useful tools for different areas in system theory, particularly multidimensional system theory. These areas range from controller design to minimal realizations of linear systems over fields. In this paper we focus on the univariate case and identify the so-called ??predictable leading monomial property?? as a property of a minimal Grobner basis that is...
This paper studies the global robust output regulation problem for a class of output feedback systems subject to an uncertain exosystem by using output feedback control. An adaptive control technique is used to handle the unknown parameter vector in the exosystem. It is shown that this unknown parameter vector can be exactly estimated asymptotically if the controller incorporates a minimal internal...
This paper addresses the problem of computing the worst-case expected value of a polynomial function, over a class of admissible distributions. It is shown that this problem, for the class of distributions considered, is equivalent to a convex optimization problem for which efficient linear matrix inequality (LMI) relaxations are available. In case that the performance function is continuous (not...
In this paper we develop a new algorithm to compute stabilizing sets for a fixed order digital controller for a multivariable plant. This computation is crucial in applications and few results are available. Our algorithm is based on (a) the Tchebyshev representation of the unit circle image of a polynomial, (b) recent results on sign-definite decomposition and (c) bounded phase results from Robust...
We show how to compute a minimal Riccati-balanced state map and a minimal Riccati-balanced state space representation starting from an image representation of a strictly dissipative system. The result is based on an iterative procedure to solve a generalization of the Nevanlinna interpolation problem.
Simultaneous localization and map building is a key issue to ensure the mobile robot move in an unknown environment autonomously. A hot topic of SLAM is how to build a map describing the complex environment. This paper presents a new SLAM algorithm using the sampled environment map, which describes the environment in detail, rather than represent the environment with a small number of geometric parameters...
In this paper, we study multiple target detection using Bayesian learning. The main aim of the paper is to present a computationally efficient way to compute the belief map update exactly and efficiently using results from the theory of symmetric polynomials. In order to illustrate the idea, we consider a simple search scenario with multiple search agents and an unknown but fixed number of stationary...
We consider decision making in a Markovian setup where the reward parameters are not known in advance. Our performance criterion is the gap between the performance of the best strategy that is chosen after the true parameter realization is revealed and the performance of the strategy that is chosen before the parameter realization is revealed. We call this gap the parametric regret. We consider two...
Finite-time stability (FTS) requires that the state of a system does not exceed a certain bound during a specified time interval for given bound on the initial state. The concept of FTS introduced exogenous inputs is called finite time boundedness (FTB). This paper gives necessary and sufficient conditions for FTB of linear time-varying continuous-time systems. The conditions are extensions of existing...
This paper places into perspective the so-called algebraic time-derivative estimation method introduced by Fliess and co-authors with standard results from linear state-space theory for control systems. In particular, it is shown that the algebraic method can essentially be seen as a special case of deadbeat state estimation based on the reconstructibility Gramian of the considered system.
Recent results on the control of linear systems subject to time-domain constraints could only handle the case of closed-loop poles that are situated on the real axis. As most closed-loop systems in practice contain also complex poles, there is a strong need for a general framework encompassing all cases. In this paper such a framework is presented based on sums-of-squares techniques and we show indeed...
Novel higher order polynomial neural network architecture is presented in this paper. The new proposed neural network is called dynamic ridge polynomial neural network that combines the properties of higher order and recurrent neural networks. The advantage of this type of network is that it exploits the properties of higher-order neural networks by functionally extending the input space into a higher...
The well known normalized monotone measures, ??-measure and P-measure, have only one formulaic solution. A multivalent normalized monotone measure with infinitely many solutions was proposed by our previous work, called L-measure, but L-measure is not a completed measure. And then, a completed measure with more many solutions than L-measure, called completed L-measure, was proposed by our next previous...
Based on the p-ary subdivision rules for B-splines, we show how to design more general subdivision schemes that preserve the B-spline smoothness exactly or almost. We illustrate the technique with new 4-point C5 binary, 4-point C3 ternary and C4 ternary subdivision schemes.
Identity-based cryptography has been gradually accepted as a more effective way of implementing asymmetric cryptography. The calculation of cryptographically-suitable pairings is crucial for the performance of pairing based protocols. In this paper we present a comparative study of hardware implementation techniques for computing the ??T pairing over the finite field F3{su97|}. Our hardware-software...
For the problem that the prediction accuracy of real-valued attribute data is not high, a modeling method named PR-KNN (polynomial regression and k nearest neighbor) is proposed, which is based on combination of KNN (k nearest neighbor) algorithm and polynomial regression model. Firstly, K nearest decision attribute values in training samples are selected by using KNN algorithm. Secondly, these K...
In the confidential computing issues of scientific computing, the confidential computing of matrix factorization is still no fruit home and abroad. This paper using Data perturbation assumption and Oblivious Transfer 1 out of k protocol, successfully construct confidential computing protocols of matrix general factorization and QR factorization. On the model of semi-honest, it can meet the confidentiality...
Fingerprinting codes are used to prevent dishonest users from redistributing copyrighted material. In this context, codes with the traceability (TA) property are of remarkable significance, since they provide an efficient way to identify traitors. Codes with the identifiable parent property (IPP) are also capable of identifying traitors, requiring less restrictive conditions than the TA codes at the...
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