Sharif Digital Repository

In this paper, two integral based methods are proposed to estimate the order and the parameters of simple fractional order models from the noisy step response data. Numerical simulation results show the efficiency of the proposed methods in the presence of the measurement noise  

This paper deals with integral based methods to estimate the order and parameters of simple fractional order models from the extracted noisy step response data of a process. This data can be obtained from both open-loop and closed-loop tests. Numerical simulation results are presented to verify the robustness of these proposed methods in the presence of the measurement noise  

This study investigates the effect of noisy measurements of the angular rate in a non-linear attitude estimator for satellites. The attitude estimator uses measurement of a single attitude sensor such as Sun, Earth-horizon, star tracker or magnetometer together with a rate gyro, and guarantees exponential convergence of the attitude estimation error to zero under a no-noise condition. In view of a realistic situation where the presence of noise in gyro measurement is not negligible, this study presents stochastic and deterministic upper bounds for the attitude estimation error resulting from noisy angular rate measurement. A realistic simulation is presented to illustrate the results  

This paper investigates the effect of noisy measurements of the angular rate in a nonlinear attitude estimator for satellites. The attitude estimator uses measurement of a single attitude sensor such as sun, earth horizon, star tracker or magnetometer together with a rate gyro, and guarantees exponential convergence of the attitude estimation error to zero under no noise condition. This paper presents stochastic and deterministic upper bounds for the attitude estimation error affected by the noise in gyro. A realistic simulation is presented to illustrate the results  

In practice, photoacoustic (PA) waves generated with cost-effective and low-energy laser diodes, are weak and almost buried in noise. Reconstruction of an artifact-free PA image from noisy measurements requires an effective denoising technique. Averaging is widely used to increase the signal-to-noise ratio (SNR) of PA signals; however, it is time consuming and in the case of very low SNR signals, hundreds to thousands of data acquisition epochs are needed. In this study, we explored the feasibility of using an adaptive and time-efficient filtering method to improve the SNR of PA signals. Our results show that the proposed method increases the SNR of PA signals more efficiently and with much... 

The Savitzky-Golay (SG) filtering is a widely used denoising method employed in different applications. The SG filter has two design parameters: the window length and the filter order. As the window length increases, the estimation variance is reduced, but at the same time, the bias error is increased. In this article, we obtain the optimal window length of an SG filter with an arbitrary order, based on minimizing the mean square error (mse), a well-known performance measure considering both the estimation bias and variance. To achieve the optimal window length, we propose an algorithm the performance of which is much better than the existing methods. In this article, we follow the viewpoint... 

We consider the problem of corrupted radar super-resolution, a generalization of compressed radar super-resolution in which one aims to recover the continuous-valued delay-Doppler pairs of moving objects from a collection of corrupted and noisy measurements. The received signal in this type consists of contributions from objects, outlier and noise. While this problem is ill-posed in general, tractable recovery is possible when both the number of objects and corrupted measurements are limited. In this brief, we propose an atomic norm optimization in order to find the delay-Doppler pairs and the outlier signal. The objective function of our optimization problem encourages both sparsity in the... 

In practice, photoacoustic (PA) waves generated with cost-effective, low-energy laser diodes, are weak and almost buried in noise. Reconstruction of an artifact-free PA image from noisy measurements requires an effective denoising technique. Averaging techniques are widely used to increase the signal-to-noise ratio (SNR) of the weak PA signals but the process is time-consuming and in case of very low SNR measurements, hundreds/thousands of data acquisition epochs needed to provide the required data In this study, we propose to use adaptive denoising methodology in which adaptive line enhancers (ALE) has been embedded for increasing the SNR of PA signals in very low-cost PA systems. Our...