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The problem of model-based fault detection in the presence of both parametric uncertainty and noise is addressed in this paper. Intervals are used to represent the uncertainty in the system parameters and interval extensions of parity equations are used as adaptive threshold selectors. A proper combination in time of different (interval) parity equations, together with a robust indicator, is used...
This paper proposes that using response surface methodology to solve multiple variables problems, for multiple responses, transforming each response into desirability function and combined them to an overall desirability function, so the multiple responses can be changed into one single function, the overall desirability is solved through intelligent algorithm. At last section, a study case is given...
In a multiuser scenario, the bit-loading, which has proven decisive in resource optimization for Power Line Communications (PLCs), has to be coupled with channel assignment to fully exploit its potential. Unfortunately, finding the most performing combination of channel and power allocation leads to integer (or mixed) programming problems, which are known to be NP-hard. To overcome the complexity...
The kinematic and dynamic analysis is applied to the task of controlling and maneuvering the quad-rotor. Here, an evaluation and discussion of the PD (Proportional Derivative) controller is used to navigate the vehicle as it performs basic translational and rotational motions. A comparison is made between the advantages and disadvantages of the controller through the evaluation of the effects of nonlinearities...
Wind blowing over the sea surface generates many dramatic effects. One of the most important effects is bubbles generated by breaking waves, which can have a major effect on high frequency acoustic propagation, sound speed profile and ambient noise due to the sound scattering and absorption properties of a thin layer of bubbles. In this paper, on one hand, we analyze several important properties of...
In this work we address the problem of state estimation in dynamical systems using recent developments in compressive sensing and sparse approximation. We formulate the traditional Kalman filter as a one-step update optimization procedure which leads us to a more unified framework, useful for incorporating sparsity constraints. We introduce three combinations of two sparsity conditions (sparsity in...
This paper discusses the use of the 3-D Matched Filter to find the velocities of targets that are traveling through an image sequence. The 3-D Matched Filter is a Fast Fourier Transform-based filter that is especially effective at reducing the random noise relative to the energy of the moving target. By testing a number of velocity vectors, it is possible to determine the velocity of a target traveling...
The channelized Hotelling observer (CHO) has become a widely used approach for evaluating medical image quality, acting as a surrogate for human observers in early-stage research on assessment and optimization of imaging devices and algorithms. Its popularity stems from experiments showing that, when an internal-noise model is introduced, the CHO's detection performance can be tuned to correlate well...
Simultaneous perturbation stochastic approximation (SPSA) has proven to be an efficient algorithm for recursive optimization. SPSA uses a centered difference approximation to the gradient based on only two function evaluations regardless of the dimension of the problem. Typically, the Bernoulli ±1 distribution is used for the perturbation vector and theory has been established to prove the asymptotic...
In cyclic (or alternating) method, the full parameter vector is divided into two or more subvectors and the process proceeds by sequentially optimizing each of the subvectors while holding the remaining parameters at their most recent values. One example of the advantage of the scheme is the preservation of large investments in software while allowing for an extension of capability to include new...
This paper addresses the energy-based localization problem in wireless sensor networks. The maximum likelihood (ML) location estimation problem is a difficult optimization problem due to the non-convexity of the objective function, and finding an exact solution is difficult. In this work, an approximate solution to the ML localization is presented, by relaxing the minimization problem into semidefinite...
This paper considers the problem of uplink scheduling in wireless networks supporting successive interference cancellation (SIC) at the physical layer. By allowing concurrent interfering transmissions, SIC enables multi-packet reception at the receiver resulting in increased network throughput. Specifically, we consider maximum throughput scheduling and proportional fair scheduling problems and study...
Energy-efficient link adaptation is studied based on minimizing the total energy consumption per transmitted bit in a mobile terminal. It is shown that the optimal power allocation is water-filling; the optimal energy consumption per bit is a function of the power amplifier efficiency, the circuit power rate dependence, and a cutoff channel to noise ratio (CNR). For a given transceiver architecture,...
Joint use of partial separability (PS) and spatial-spectral sparsity constraints has previously been demonstrated useful for image reconstruction from undersampled data. This paper extends our early work in this area by proposing a new method for jointly enforcing the PS and spatial total variation (TV) constraints for dynamic MR image reconstruction. An algorithm is also described to solve the underlying...
The minimization of the overall power consumption of wireless networks while satisfying a certain throughput and error rate constraint is investigated. The total power dissipation includes the radiated power as well as the circuit power consumption. In the context of battery operated short range communication, where low power, low cost and small size are key requirements (e.g. standard IEEE 802.15...
This paper presents an adaptive background update method for waves extraction based on the physical properties of tide. Most of the previous background subtraction methods based on analysis of regional connectivity detect a wave period using a static background templates or a feature set of moving objects. However, random wave in such tide videos are not extracted well. In this paper, we assume that...
In enclosed environments where robots are deployed, the observed speech signal is smeared due to reverberation. This degrades the performance of the automatic speech recognition (ASR). Thus, hands-free speech recognition for human-machine communication is a difficult task. Most speech enhancement techniques used to address this problem enhance the contaminated waveform independent from that of the...
The proper management of the signal to noise ratio margin is important for improving the stability of digital subscriber line (DSL) networks and increasing the customer satisfaction regarding services such as triple-play. This work presents a novel algorithm for multiuser margin optimization that benefits from the relationships between power and margin adaptation. The proposed multiuser margin maximization...
Solving the vision problem using convex optimization theory is now a focus in computer vision and robot communities. Second Order Cone Programming (SOCP) is especially effective in these methods. This paper discusses homography estimation in omnidirectional vision under the L∞-norm, which provides a theoretical guarantee of global optimality and a wide field of view. We give three different kinds...
Computational fluid dynamics (CFD) simulators have recently been used for optimization in die casting and various other fields. However, solving an optimization problem with a CFD simulator (CFD optimization problem) has the issue of uncertainty in the evaluated values from the CFD simulations. Such problems are, of course, difficult to optimize compared to general problems. In this paper, we propose...
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