Research Interest

The problem of "Sampling and Reconstruction" of any signal lies in heart of signal analysis and communication theory. It deals with the following two natural questions:

1. Can we approximate a complicated function by a 'nice' function using available sample values of the given function ??

2. Is the exact recovery of the original signal possible without losing information in the process in case the sample values are known ??

• Currently, I am interested in Question (2), particularly in the realm of "Random Sampling and Reconstruction of signals lying in different function spaces" by exploiting the tools of Real analysis, Functional analysis, and Operator theory mainly. Random sampling problem involves the recovery of a signal in case of randomly distributed sample values.

• During my doctoral studies, I focused on Question (1) and studied the approximation behavior of certain families of infinite sampling series. It includes Kantorovich as well as type Durrmeyer type sampling operators, and the sampling operators induced by neural networks activated by sigmoidal functions.

" In order to make the sampling-reconstruction problem interesting, it is always good to change the underlying function space and the pattern of sampling set at the disposal. I am looking for a new set-up to analyze the aforesaid problem..."