Frame-adaptive techniques for quality versus efficiency tradeoffs in STFT analysis

In this paper, we present techniques for computing frame-adaptive approximations to the STFT which can satisfy arbitrarily specified bounds on the number of arithmetic operations per frame. The central idea is to represent the samples in each signal frame with a very small number Q of quantization levels, yielding an SNR of 10Iog(Q²) dB. This leads to the formulation of the frame´s DFT computation as a process of summation among pre-stored vectors. Experimental studies are used to propose and verify mathematical models for how the number of vector additions needed in this process depends on the frequency content of a frame. The models are utilized to design frame-adaptive techniques for excluding various subsets of vector elements from the summation process in order to keep the number of additions per frame from exceeding any specified bound, B