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This paper considers a scenario in which signals from an emitter at an unknown location are received at a number of different collinear locations. The receiver can determine the received signal strength, but no other parameters of the signal. Postulating a log-normal transmission model with a constant but unknown path loss exponent and, also, an unknown transmit power and known noise variance, the...
This paper considers the localization performance of MIMO radars with widely-separated antennas. A Multiple-Hypothesis (MH) based algorithm is proposed for multiple target localization problems where targets become unobservable in certain pairs of transmitters and receivers. In addition, the performance of MIMO radars in localizing multiple-scatterer targets is compared to that of multistatic radar...
Mid-term load forecasting is taken into account as one of the most important policies in the electricity market and brings about many financial, commercial and, even, political benefits. In this paper, artificial neural networks are represented for mid-term load forecasting of Iran national power system. To do so, the multi layer perceptron (MLP) neural network as well as radial basis function (RBF)...
In this paper, stochastic control of nonlinear state space models is discussed. After a brief review on nonlinear state space models, a multi layer perceptron (MLP) neural network is considered to represent the general structure of the controller. Then, an expectation maximization (EM) algorithm joint with the particle smoothing framework are proposed for updating parameters of the MLP network. The...
Identification of nonlinear state space models when no information is available from the state transition or output model has played an important role in the recent research. In this paper, we propose a new approach for modeling a discrete time nonlinear state space system with a multi layer perceptron (MLP) neural network. The expectation maximization (EM) algorithm is used for joint parameter and...
Short term load forecasting (STLF) plays an important role for the power system operational planners and also most of the participants in the nowadays electricity markets. With the importance of the STLF in power system operation and electricity markets, many methods for arriving careful results, are represented. In this paper, a combination approach for STLF is proposed. The proposed approach is...
Flow shop production lines are very common in manufacturing systems such as car assemblies, manufacturing of electronic boards, etc. In such systems all jobs (products) visit the workstations in the same sequence. In this paper, we address the problem of uncertainties in controlling the flow shop production systems. The contribution of this work is to propose two novel approaches for controlling the...
Flow shop production lines are very common in manufacturing systems such as car assemblies, manufacturing of electronic circuits, etc. In this paper. To model the uncertainty embedded in service times, all service times are first considered in the form of fuzzy numbers. Also, a systematic procedure is given for generating event-timing equations directly from the machine interconnections for a generalized...
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