• Title/Summary/Keyword: optimal linear combination

Search Result 122, Processing Time 0.019 seconds

STRONG CONTROLLABILITY AND OPTIMAL CONTROL OF THE HEAT EQUATION WITH A THERMAL SOURCE

  • Kamyad, A.V.;Borzabadi, A.H.
    • Journal of applied mathematics & informatics
    • /
    • v.7 no.3
    • /
    • pp.787-800
    • /
    • 2000
  • In this paper we consider an optimal control system described by n-dimensional heat equation with a thermal source. Thus problem is to find an optimal control which puts the system in a finite time T, into a stationary regime and to minimize a general objective function. Here we assume there is no constraints on control. This problem is reduced to a moment problem. We modify the moment problem into one consisting of the minimization of a positive linear functional over a set of Radon measures and we show that there is an optimal measure corresponding to the optimal control. The above optimal measure approximated by a finite combination of atomic measures. This construction gives rise to a finite dimensional linear programming problem, where its solution can be used to determine the optimal combination of atomic measures. Then by using the solution of the above linear programming problem we find a piecewise-constant optimal control function which is an approximate control for the original optimal control problem. Finally we obtain piecewise-constant optimal control for two examples of heat equations with a thermal source in one-dimensional.

Structuring Element Representation of an Image and Its Applications

  • Oh, Jin-Sung
    • International Journal of Control, Automation, and Systems
    • /
    • v.2 no.4
    • /
    • pp.509-515
    • /
    • 2004
  • In this paper we present the linear combination of a fuzzy opening and closing filter with locally adaptive structuring elements that can preserve the geometrical features of an image. Based on the adaptation algorithm of linear combination of the fuzzy opening and closing filter, the optimal structuring element for image representation is obtained. The optimal structuring element is an indicator of the shape and direction of an object's image, which is useful in filtering, multi resolution, segmentation, and recognition of an image.

The Optimal Combination of Neural Networks for Next Day Electric Peak Load Forecasting

  • Konishi, Hiroyasu;Izumida, Masanori;Murakami, Kenji
    • Proceedings of the IEEK Conference
    • /
    • 2000.07b
    • /
    • pp.1037-1040
    • /
    • 2000
  • We introduce the forecasting method for a next day electric peak load that uses the optimal combination of two types of neural networks. First network uses learning data that are past 10days of the target day. We name the neural network Short Term Neural Network (STNN). Second network uses those of last year. We name the neural network Long Term Neural Network (LTNN). Then we get the forecasting results that are the linear combination of the forecasting results by STNN and the forecasting results by LTNN. We name the method Combination Forecasting Method (CFM). Then we discuss the optimal combination of STNN and LTNN. Using CFM of the optimal combination of STNN and LTNN, we can reduce the forecasting error.

  • PDF

Reconstruction of High-Resolution Facial Image Based on A Recursive Error Back-Projection

  • Park, Joeng-Seon;Lee, Seong-Whan
    • Proceedings of the Korean Information Science Society Conference
    • /
    • 2004.04b
    • /
    • pp.715-717
    • /
    • 2004
  • This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

  • PDF

An Evaluatiou of Parameter Variations for a Linear Reservoir (TANK) Model with Watershed Characteristics (유역특성에 따른 탱크모형 매개변수의 변화)

  • 김현영;박승우
    • Magazine of the Korean Society of Agricultural Engineers
    • /
    • v.28 no.2
    • /
    • pp.42-52
    • /
    • 1986
  • This study involves the estimation of optimal ranges of parameters for a linear watershed model. A well-known TANK model was chosen and a linear combination of four tanks assumed. The model was used to simulate daily streamflow for six watersheds of different sizes and by a trial-and-error approach a set of optimal parameters defined. The parameters were related to watershed sizes and land use conditions. Optimal parameters for ungaged conditions were defined from the relationships; daily streamflow simulated and compared to the observed date. The simulated results were in a general agreement with the data.

  • PDF

Beam-rotating machinery system active vibration control using a fuzzy input estimation method and LQG control technique combination

  • Lee, Ming-Hui
    • Smart Structures and Systems
    • /
    • v.10 no.1
    • /
    • pp.15-31
    • /
    • 2012
  • This study proposes an active control method to suppress beam-rotating machinery system vibrations. The present control method is a combination of the fuzzy input estimation method (FIEM) and linear quadratic Gaussian problem (LQG) algorithms. The FIEM can estimate the unknown input and optimal states by measuring the dynamic displacement, the optimal estimated states into the feedback control; thereby obtaining the optimal control force for a random linear system. Active vibration control of a beam-rotating machinery system is performed to verify the feasibility and effectiveness of the proposed algorithm. The simulation results demonstrate that the proposed method can suppress vibrations in a beam-machine system more efficiently than the conventional LQG method.

A NEW APPROACH FOR ASYMPTOTIC STABILITY A SYSTEM OF THE NONLINEAR ORDINARY DIFFERENTIAL EQUATIONS

  • Effati, Sohrab;Nazemi, Ali Reza
    • Journal of applied mathematics & informatics
    • /
    • v.25 no.1_2
    • /
    • pp.231-244
    • /
    • 2007
  • In this paper, we use measure theory for considering asymptotically stable of an autonomous system [1] of first order nonlinear ordinary differential equations(ODE's). First, we define a nonlinear infinite-horizon optimal control problem related to the ODE. Then, by a suitable change of variable, we transform the problem to a finite-horizon nonlinear optimal control problem. Then, the problem is modified into one consisting of the minimization of a linear functional over a set of positive Radon measures. The optimal measure is approximated by a finite combination of atomic measures and the problem converted to a finite-dimensional linear programming problem. The solution to this linear programming problem is used to find a piecewise-constant control, and by using the approximated control signals, we obtain the approximate trajectories and the error functional related to it. Finally the approximated trajectories and error functional is used to for considering asymptotically stable of the original problem.

Soft Combination Schemes for Cooperative Spectrum Sensing in Cognitive Radio Networks

  • Shen, Bin;Kwak, Kyung-Sup
    • ETRI Journal
    • /
    • v.31 no.3
    • /
    • pp.263-270
    • /
    • 2009
  • This paper investigates linear soft combination schemes for cooperative spectrum sensing in cognitive radio networks. We propose two weight-setting strategies under different basic optimality criteria to improve the overall sensing performance in the network. The corresponding optimal weights are derived, which are determined by the noise power levels and the received primary user signal energies of multiple cooperative secondary users in the network. However, to obtain the instantaneous measurement of these noise power levels and primary user signal energies with high accuracy is extremely challenging. It can even be infeasible in practical implementations under a low signal-to-noise ratio regime. We therefore propose reference data matrices to scavenge the indispensable information of primary user signal energies and noise power levels for setting the proposed combining weights adaptively by keeping records of the most recent spectrum observations. Analyses and simulation results demonstrate that the proposed linear soft combination schemes outperform the conventional maximal ratio combination and equal gain combination schemes and yield significant performance improvements in spectrum sensing.

  • PDF

Characterization of Korean Clays and Pottery by Neutron Activation Analysis(II). Characterization of Korean Potsherds

  • Lee, Chul;Kwun, Oh-Cheun;Kim, Seung-Won;Lee, Ihn-Chong;Kim, Nak-Bae
    • Bulletin of the Korean Chemical Society
    • /
    • v.7 no.5
    • /
    • pp.347-353
    • /
    • 1986
  • Fisher's discriminant method has been applied to the problem of the classification of Korean potsherds, using their elemental composition as analyzed by neutron activation analysis. A combination of analytical data by means of statistical linear discriminant analysis has resulted in removal of redundant variables, optimal linear combination of meaningful variables and formulation of classification rules.

IMPROVING THE ESP ACCURACY WITH COMBINATION OF PROBABILISTIC FORECASTS

  • Yu, Seung-Oh;Kim, Young-Oh
    • Water Engineering Research
    • /
    • v.5 no.2
    • /
    • pp.101-109
    • /
    • 2004
  • Aggregating information by combining forecasts from two or more forecasting methods is an alternative to using forecasts from just a single method to improve forecast accuracy. This paper describes the development and use of a monthly inflow forecast model based on an optimal linear combination (OLC) of forecasts derived from naive, persistence, and Ensemble Streamflow Prediction (ESP) forecasts. Using the cross-validation technique, the OLC model made 1-month ahead probabilistic forecasts for the Chungju multi-purpose dam inflows for 15 years. For most of the verification months, the skill associated with the OLC forecast was superior to those drawn from the individual forecast techniques. Therefore this study demonstrates that OLC can improve the accuracy of the ESP forecast, especially during the dry season. This study also examined the value of the OLC forecasts in reservoir operations. Stochastic Dynamic Programming (SDP) derived the optimal operating policy for the Chungju multi-purpose dam operation and the derived policy was simulated using the 15-year observed inflows. The simulation results showed the SDP model that updated its probability from the new OLC forecast provided more efficient operation decisions than the conventional SDP model.

  • PDF