The ability to process signals at multiple sampling rates can help reduce costs and improve performance in many DSP applications ranging from signal compression to wireless communications, consumer entertainment products and sensor networks. The theory of multirate signal processing has witnessed a great deal of progress since the publication of the first textbook by Ronald E. Crochiere and Lawrence R. Rabiner in 1983. However, this progress has been mainly in the area of deterministic systems with emphasis on perfect-reconstruction filter banks, orthogonal filter banks, systems with the same sampling rate across all channels and tree-structured systems.
Multirate Statistical Signal Processing introduces a statistical theory for extracting information from several related signals that have different sampling rates. This new theory generalizes the conventional (deterministic) theory of multirate systems beyond many of its constraints. Furthermore, it allows for the formulation and solution of several new problems such as spectrum estimation, time-delay estimation and sensor fusion in the realm of multirate signal processing.
The author presents background material, key principles, potential applications and leading-edge research while striking the appropriate balance between clarity and brevity. The book is self-contained and provides a valuable resource for signal processing researchers, graduate students and practicing engineers.