Discrete-time signal processing
Discrete-time signal processing
Subband DFT—part I: definition, interpretation and extensions
Signal Processing
Subband DFT—part II: accuracy, complexity and applications
Signal Processing
Digital signal processing (3rd ed.): principles, algorithms, and applications
Digital signal processing (3rd ed.): principles, algorithms, and applications
Speech Processing
Multirate Signal Processing for Communication Systems
Multirate Signal Processing for Communication Systems
Signal Processing - Signal processing in communications
Digital Signal Processing Using MATLAB and Wavelets (Electrical Engineering)
Digital Signal Processing Using MATLAB and Wavelets (Electrical Engineering)
Digital Signal and Image Processing Using MATLAB (Digital Signal and Image Processing series)
Digital Signal and Image Processing Using MATLAB (Digital Signal and Image Processing series)
Efficient computation of the DFT with only a subset of input oroutput points
IEEE Transactions on Signal Processing
A novel generic fast Fourier transform pruning technique and complexity analysis
IEEE Transactions on Signal Processing
On homomorphic deconvolution of bandpass signals
IEEE Transactions on Signal Processing
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In this paper we present a new fast approximate inverse FFT for short-time signal applications. This approach is derived from the sub-band FFT SB-FFT and it is called Sub-Segment IFFT SS-IFFT. SS-IFFT uses the idea of decomposing the input signal into two segments early and late according to their order of occurence in time. An approximation can be done by implementing the IFFT of one of the two-segments according to a pre-known information about the time-domain characteristics of the signal. Such an approximation leads to fast computation at the cost of less accuracy. Both the reduction in complexity and the approximation errors of the new algorithm are investigated in this paper. The SS-IFFT has an adaptive capability like the forward SB-FFT. The idea of SS-IFFT is extended also to the two dimensional case. The algorithm is also tested by using different filters other than the Hadamard filters used in the SB-FFT. Different applications of the new technique are included in speech analysis, echo detection, FIR filter design, and ECG compression.