Bøger af Atanu Das

Some salient contributions of this work are modification and characterization of Adaptive Kalman Filter (AKF) and application thereof in modelling and estimation of financial time series. The failure cases of AKF's have been identified and characterized. Modifications are then made to avoid the singularity, without affecting the essential performance of AKFs. These modified varieties of AKF techniques were characterized using both synthetic data and empirical data from Indian financial market. Performances of the existing and modified AKF methods are compared with the benchmark approaches and conventional adaptive methods (like Recursive Least Square and Least Mean Square) for beta and volatility (and hence VaR) estimation. Performances of the conventional and evolved adaptive methods have been compared with the performances of benchmark methods and advantages of the adaptive methods have been pointed out. The analysis would hopefully provide better understanding of Indian financial markets and permit better financial decisions.

Biomedical control systems are inherently non linear and carry normal input signals for smooth functioning of the system. Alteration of the normal actuating signal may not be permitted there. We can modify the performance at desired level by injecting an additional signal at the system input without affecting the normal input signals. This book deals with the development of a novel technique for such modifications. The technique is named as ¿Signal Correction Technique (SCT)¿, because desired response for appropriate performance of a system is achieved by the application of correcting signal in addition to the existing one. Some applications of the developed technique are also explored in this book.