Aliasing reduction in soft-clipping algorithms

Esqueda, Fabian; Välimäki, Vesa; Bilbao, Stefan

doi:10.1109/eusipco.2015.7362737

Cited by 7 publications

(12 citation statements)

References 6 publications

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“…The polyBLAMP is shown to effectively reduce aliasing distortion in hard-clipped signals with less computational costs than when oversampling. The first case of the BLAMP method (2-point correction) was published recently elsewhere [19], and the present paper generalizes and expands these results. This paper is organized as follows.…”

Section: Introductionsupporting

confidence: 71%

“…For each set of clipping boundaries, the associated slope and fractional delay are estimated using (17) and (19), respectively. These parameters are then used to compute the polyBLAMP correction coefficients, which are added to the clipped signal at the boundaries.…”

Section: A Two-point Polynomial Correctionmentioning

confidence: 99%

“…8 to emphasize their independence from the actual polyBLAMP method. Table II shows pseudocode for the 2-point polyBLAMP method using (17) and (19) to estimate parameters µ and d, respectively. In this example, the "Clipping boundary detection" stage (see Fig.…”

Section: A Two-point Polynomial Correctionmentioning

confidence: 99%

“…Often hard clipping is used in connection with soft clipping so that the latter works at small signal values while the former saturates (clips) the large signal values to a maximum or minimum value. Antialiasing for the combination of a soft and a hard clipper in this context was the first application for the method discussed in this paper [19]. Similar saturating modules appear in physical models of musical wind and string instruments in which a saturating waveshaper simulates the nonlinear interaction between the excitation and state of an acoustic resonator, such as a tube or a string [20], [21].…”

Section: Introductionmentioning

confidence: 99%

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Aliasing Reduction in Clipped Signals

Esqueda¹,

Bilbao

Välimäki³

2016

IEEE Trans. Signal Process.

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An aliasing reduction method for hard-clipped sampled signals is proposed. Clipping in the digital domain causes a large amount of harmonic distortion, which is not bandlimited, so spectral components generated above the Nyquist limit are reflected to the baseband and mixed with the signal. A model for an ideal bandlimited ramp function is derived, which leads to a post-processing method to reduce aliasing. A number of samples in the neighborhood of a clipping point in the waveform are modified to simulate the Gibbs phenomenon. This novel method requires estimation of the fractional delay of the clipping point between samples and the first derivative of the original signal at that point. Two polynomial approximations of the bandlimited ramp function are suggested for practical implementation. Validation tests using sinusoidal, triangular, and harmonic signals show that the proposed method achieves high accuracy in aliasing reduction. The proposed 2-point and 4-point polynomial correction methods can improve the signal-to-noise ratio by 12 dB and 20 dB in average, respectively, and are more computationally efficient and cause less latency than oversampling, which is the standard approach to aliasing reduction. An additional advantage of the polynomial correction methods over oversampling is that they do not introduce overshoot beyond the clipping level in the waveform. The proposed techniques are useful in audio and other fields of signal processing where digital signal values must be clipped but aliasing cannot be tolerated.

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Section: Introductionsupporting

confidence: 71%

Section: A Two-point Polynomial Correctionmentioning

confidence: 99%

Section: A Two-point Polynomial Correctionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Aliasing Reduction in Clipped Signals

Esqueda¹,

Bilbao

Välimäki³

2016

IEEE Trans. Signal Process.

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“…Any nonlinearities in a pickup model will cause bandwidth expansion and add to the characteristic sound of the Hammond organ. In the case that this bandwidth expansion would go beyond the Nyquist limit, alias-suppression methods become relevant [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Modal Processor Effects Inspired by Hammond Tonewheel Organs

Werner

Abel

2016

Applied Sciences

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Abstract:In this design study, we introduce a novel class of digital audio effects that extend the recently introduced modal processor approach to artificial reverberation and effects processing. These pitch and distortion processing effects mimic the design and sonics of a classic additive-synthesis-based electromechanical musical instrument, the Hammond tonewheel organ. As a reverb effect, the modal processor simulates a room response as the sum of resonant filter responses. This architecture provides precise, interactive control over the frequency, damping, and complex amplitude of each mode. Into this framework, we introduce two types of processing effects: pitch effects inspired by the Hammond organ's equal tempered "tonewheels", "drawbar" tone controls, vibrato/chorus circuit, and distortion effects inspired by the pseudo-sinusoidal shape of its tonewheels and electromagnetic pickup distortion. The result is an effects processor that imprints the Hammond organ's sonics onto any audio input.

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Nonlinear signal processing with minimization of spectral distortion for embedded systems

Konopko

Janczak

2018

IFAC-PapersOnLine

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Aliasing reduction in soft-clipping algorithms

Cited by 7 publications

References 6 publications

Aliasing Reduction in Clipped Signals

Aliasing Reduction in Clipped Signals

Modal Processor Effects Inspired by Hammond Tonewheel Organs

Nonlinear signal processing with minimization of spectral distortion for embedded systems

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