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In this short note, we have proposed an approach to find the solution for constant gain stabilization problem with desired damping. This short note illustrates that it is easy to find the bound on the constant gain as compared to Aniruddha Datta's proposed method.

In this paper a new algorithm is proposed to remove Gaussian noise with edge preservation. The function of the proposed algorithm is to first find the pixel values along the boundary of the filtering window and then calculate its variance. If this variance is less than a threshold specified, then the corrupted pixel is replaced by the mean of the inside pixels from the filtering window after sorting and trimming. Experimental results shows that the proposed algorithm outperforms with significant improvement in image quality than the arithmetic mean, alpha-trimmed mean filter, wiener filter, K-means filter and adaptive window based method. The proposed method removes the Gaussian noise very effectively even at a noise variance as high as 40 with edge preservation.

In this paper a new efficient algorithm for the removal of Gaussian noise in gray scale and color images using adaptive window is presented. The function of the algorithm is to replace each corrupted pixel by a mean value of the pixels inside an adaptive window. The adaptive window is formed using a threshold calculated form noise variance. The proposed algorithm is simple and it works very effectively in removing Gaussian noise compare with the other techniques. The proposed algorithm is tested for both gray scale and color images corrupted with Gaussian noise. The visual and quantitative results show that the proposed algorithm performs well in removing Gaussian noise and preserve edge details.

This paper deals with a method of estimation of robust dead-time for first order plus time delay (FOPTD) process which does not violate the closed loop stability when Proportional-Integral (PI) parameters and Proportional-Integral-Derivative (PID) parameters as suggested by popular tuning techniques, have been used. Using the Hermite-Biehler Theorem applicable to quasi polynomials, we estimate the lower bound value of (T/L) and then the range of L for the two controller modes. This investigation will help to infer the amount of system parameters that can be tolerated before control system becomes unstable for the two controller modes.