Discrete-Time Signal Processing¶
Oppenheim, A. V., & Schafer, R. W. (2009). Discrete-Time Signal Processing. Prentice Hall.
Cited by¶
7 citations across 7 artifacts.
Each citation links to the sentence it supports in the citing article.
Primes¶
- Aliasing
- In audio signal processing it is canonical: a tone above half the sampling rate folds into the audible band — a 45 kHz component sampled at 44 kHz appears as a clean 1 kHz tone — which is why analog-to-digital converters place an anti-aliasing low-pass filter before the sampler.
This sourceStandard reference for aliasing, frequency folding, the anti-aliasing filter, and the worked sinusoid-undersampling case (a high tone folding to a low one).
- In audio signal processing it is canonical: a tone above half the sampling rate folds into the audible band — a 45 kHz component sampled at 44 kHz appears as a clean 1 kHz tone — which is why analog-to-digital converters place an anti-aliasing low-pass filter before the sampler.
- Discretization-Induced Artifact
Domain-specific¶
- Lag windowing
- Nonrecursive (FIR) Filter
This sourceStandard authority for LTI convolution, FIR/IIR systems, z transforms, structures, and linear phase.
- Phase response
Mechanisms¶
- Finite Impulse Response Filter
- Its failure mode is the price of a sharp, finite cutoff: truncating an ideal filter to a finite tap set produces ringing overshoot near sharp transitions, the Gibbs phenomenon.
This sourceExplains that truncating an ideal infinite-duration response to a finite FIR design produces oscillatory overshoot near sharp cutoffs—the Gibbs phenomenon.
- Its failure mode is the price of a sharp, finite cutoff: truncating an ideal filter to a finite tap set produces ringing overshoot near sharp transitions, the Gibbs phenomenon.
- Rolling-Window Rate Estimator
- A boxcar window gives an event its full weight for W seconds and then drops it instantly, so a genuine spike that scrolls off the trailing edge causes the rate to fall off a cliff a full W later — a lag and a phantom "drop" that never happened.
This sourceExplains the boxcar window's hard trailing edge: a sample retains full weight throughout the window and disappears abruptly when it scrolls out.
- A boxcar window gives an event its full weight for W seconds and then drops it instantly, so a genuine spike that scrolls off the trailing edge causes the rate to fall off a cliff a full W later — a lag and a phantom "drop" that never happened.
Verification¶
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Does it back the claim? Not recorded. Neither this nor any other of the 7 citations of this work carries a recorded support check.
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Links previously used in the corpus¶
Before the registry existed this work was also linked 3 other ways.
- https://www.pearson.com/en-us/subject-catalog/p/discrete-time-signal-processing/P200000003226 ×2
- https://books.google.com/books/about/Discrete_time_Signal_Processing.html?id=mYsoAQAAMAAJ ×1
- https://www.pearson.com/subject-catalog/p/discrete-time-signal-processing/P200000003226/9780137549771 ×1
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