Signal processing is the technology of the future. Many inventions of mankind have been possible due to the beautiful signal processing frameworks developed over the course of scientific evolution. For example "Curiosity" rover on planet Mars being controlled on earth is one of the marvel application of signal processing.

Signal processing applications are manifold whose applications are multi-disciplinary: cellular communications, medical applications, IoT, speech technology etc. We at SPCRC work on the various start of art problems in signal processing relevant to futuristic technologies.

An early breakthrough in signal processing was the Nyquist–Shannon sampling theorem. It states that if a real signal's highest frequency is less than half of the sampling rate (or less than the sampling rate, if the signal is complex), then the signal can be reconstructed perfectly by means of sinc interpolation. The main idea is that with prior knowledge about constraints on the signal's frequencies, fewer samples are needed to reconstruct the signal.

Around 2004, Emmanuel Candès, Justin Romberg, Terence Tao, and David Donoho proved that given knowledge about a signal's sparsity, the signal may be reconstructed with even fewer samples than the sampling theorem requires. This idea is the basis of compressed sensing. [ref]