George Saon, Mukund Padmanabhan
NeurIPS 2000
A generalized filter-bank structure is developed, to implement an arbitrary transform in a time-recursive manner. It is based on the NxN basis matrix of the transform, and for the general case, has a complexity of O(N 2); however, its complexity reduces considerably, to approximately 47V - 57V, for the case of trigonometric transforms such as the DFT, DCT, and DST. As far as hardware complexity is concerned, it is similar to frequency sampling structures, but unlike them, it has much better behavior under finite precision arithmetic; it remains stable under coefficient truncation, and also does not sustain limit cycles if magnitude truncation is applied. The linear complexity, modularity, and good finite precision behavior of the structure make it extremely suitable for implementation using VLSI circuits or digital signal processors. © 1993 IEEE
George Saon, Mukund Padmanabhan
NeurIPS 2000
Geoffrey Zweig, Jing Huang, et al.
INTERSPEECH - Eurospeech 2001
George Saon, Mukund Padmanabhan
IEEE Transactions on Speech and Audio Processing
Mukund Padmanabhan, Satya Dharanipragada
IEEE Transactions on Speech and Audio Processing