Signal Processing

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27 domain-specific abstractions whose origin domain is Signal Processing.

• Adaptive feedback cancellation — An electro-acoustic control method that continually estimates a time-varying feedback path and subtracts its predicted contribution to suppress howling while preserving the desired signal.
• Bruun's FFT algorithm — A fast Fourier transform based on recursive real-coefficient factorization of the transform polynomial, postponing complex arithmetic until a final reconstruction stage.
• Chirplet transform — A time-frequency transform correlating a signal with localized chirps whose frequency changes within each analysis atom.
• Circular convolution — A convolution on periodic sequences in which indices wrap modulo a fixed length, corresponding to pointwise multiplication under the discrete Fourier transform.
• Colors of noise — A classification of stochastic signals by the frequency dependence of their power spectral density.
• Constant-Q transform — A time–frequency transform whose analysis bins maintain a constant ratio of center frequency to bandwidth, producing logarithmic frequency resolution.
• Dependent component analysis — A blind-source-separation method recovering mutually independent groups of components while allowing dependence among members of each group.
• Discrete Fourier transform — An invertible linear transformation between a finite sequence and coefficients on equally spaced discrete frequencies.
• Discrete-time Fourier transform — A periodic continuous-frequency function obtained by summing a discrete-time sequence against complex exponentials, representing the sequence by its spectral amplitudes.
• Gabor wavelet — A complex sinusoid localized by a Gaussian envelope, providing near-minimal joint uncertainty in position or time and spatial or temporal frequency.
• Hilbert spectral analysis — A time–frequency analysis that forms analytic signals, often from empirical mode components, and derives instantaneous amplitude and frequency from Hilbert phase.
• Lanczos resampling — Signal resampling by convolution with a finite-windowed sinc kernel.
• Log Gabor filter — A band-pass signal filter whose transfer function is Gaussian on a logarithmic frequency axis, providing no DC component and flexible bandwidth for localized multi-scale analysis.
• Lulu smoothing — A nonlinear sequence smoother built from alternating local lower and upper envelope operators that remove impulsive noise while preserving step structure.
• Mean square quantization error — Evaluate a quantizer by averaging the squared difference between each input and its reconstruction value under a declared input distribution, making large reconstruction deviations contribute quadratically.
• Modified Discrete Cosine Transform — Map each 50%-overlapped real-signal block to a critically sampled cosine-coefficient block so that the apparent time-domain aliasing of each inverse block cancels when adjacent, compatibly windowed blocks are overlapped and added.
• Modified Wigner distribution function — A member of a modified quadratic time–frequency representation family designed to suppress the interference cross-terms of the Wigner distribution while retaining useful concentration.
• Non-separable wavelet — A multidimensional wavelet whose analyzing function or filter bank cannot be factored into tensor products of lower-dimensional wavelets.
• Oversampling — Sampling a signal substantially above its Nyquist rate to ease antialias filtering, distribute quantization noise and improve effective resolution after filtering or decimation.
• Phase response — The frequency-dependent phase difference between a system's sinusoidal output and input, forming the angular component of its complex transfer function.
• Polyphase matrix — A matrix of polyphase filter components that represents a multirate filter bank, making downsampling structure, perfect reconstruction and efficient implementation algebraically explicit.
• Rectangular function — A piecewise-constant pulse equal to one on a centered finite interval and zero outside, with a convention-dependent value at the endpoints.
• Sampling (signal processing) — The representation of a continuous-domain signal by values taken at discrete time, space or other-domain locations.
• Signal averaging — The recovery of a repeatable signal by aligning repeated observations and averaging them so uncorrelated zero-mean noise cancels.
• Time–frequency analysis — Represent a nonstationary signal jointly over time and frequency so changing spectral content, transients, and localization tradeoffs remain visible instead of being collapsed into one global spectrum.
• Total variation denoising — A signal-reconstruction method that balances fidelity to observed data against a penalty on total variation so noise is reduced while sharp edges are retained.
• Z-transform — Represent a discrete-time sequence by a Laurent series in a complex variable together with its region of convergence, enabling shifts, convolution, recurrences, spectra, and system behavior to be analyzed algebraically.