Discrete-time signal processing (2nd ed.)

By A. Oppenheim, R. Schafer, J. Buck. 1999

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Citations in the corpus

Time-Frequency Masking in the Complex Domain for Speech Dereverberation and Denoising (2017, neutral): “components (one for each signal) and using the distributive property of convolution [30].”
The sliding DFT (2003, methodology): “The derivation of this filter’s structure is readily available in the literature [5]-[7].”
A systemic view of the ADIDA framework (2014, methodology): “Moreover, this formulation reveals the astounding similarities of the ADIDA framework with multi-rate signal processing techniques (Crochiere & Rabiner, 1983; Oppenheim & Schafer, 1999).”
Spacetime Forests with Complementary Features for Dynamic Scene Recognition (2013, background): “This interpretation is justified by Parseval’s theorem [25], which states that the sum of the squared values over the spacetime domain is proportional to the sum of the squared magnitude of the Fourier components over the frequency domain; in the present case, the squared values of the orientation s”
Full duplex radios (2013, background): “The Nyquist theorem [13] tells us that sampling (at the Nyquist rate) does not lose information, in other words we can always reconstruct the signal at any instant as a weighted linear combination of samples taken before and after the instant at which we want to recreate.”
SPIRAL: Code Generation for DSP Transforms (2005, methodology): “…as the column vector h = [ h l ; : : : ; h 0 ; : : : ; h (cid:0) r ] T of length l + r + 1 , or as the z - transform polynomial h [ z ] (e.g., [31]), The output of the FIR ﬁlter for n output points is computed by multiplying the relevant (i.e., contributing to these outputs) ﬁnite subvector…”
Adaptive boosting for SAR automatic target recognition (2007, background): “Next, we compute the two-dimensional DFT for the cropped image.”
Extension of phase correlation to subpixel registration (2002, background): “Note that compactly supported signals and periodic signals are treated in the same manner in the context of DFT (see [18, Ch. 8]).”
The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference. (2014, methodology): “20), and the Convolution Theorem (Oppenheim et al., 1998), we have:”
Effect of Mode Coupling on Signal Processing Complexity in Mode-Division Multiplexing (2013, methodology): “In processing each block, these operations equalize symbols, so the number of complex multiplications per symbol is [42], [46]:”
Compression Artifacts in Perceptual Audio Coding (2008, background): “The first artifact resembles the Gibbs phenomenon [43], which has a high noise level at the edge of the attack signal.”
Full-Duplex Wireless Communications: Challenges, Solutions, and Future Research Directions (2016, methodology): “relying on Nyquist sampling theorem [77]), we can always reconstruct the SI signal at any instant as a weighted linear combination of samples taken before and after the recreation instant, with the weights of the linear combination determined by using the so calledsince interpolationalgorithm.”
Is Orbital Angular Momentum (OAM) Based Radio Communication an Unexploited Area? (2012, unknown): “[15], which was also observed in [1].”
Quantification of Tremor and Bradykinesia in Parkinson's Disease Using a Novel Ambulatory Monitoring System (2007, methodology): “To find the instantaneous amplitude of the low-pass filtered signal of the gyroscope , an analytical signal was constructed [26]”