Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Yuta Hatano

dblp:173/6926 · DBLP profile ↗
← Back
1ranked-venue papers
1as first author
0since 2021 · last 2017
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Audio and music processing › acoustic signal processing
nonlinear distortion compensation
0.312017
Compensation for Nonlinear Distortion of the Frequency Modulation-Based Parametric Array Loudspeaker · IEEE ACM Trans. Audio Speech Lang. Process. 2017
Audio and music processing › audio reproduction
parametric loudspeaker
0.312017
Compensation for Nonlinear Distortion of the Frequency Modulation-Based Parametric Array Loudspeaker · IEEE ACM Trans. Audio Speech Lang. Process. 2017

Methods — techniques the papers use, named apart from their topics

volterra filter · 0.3parallel cascade structure · 0.3inverse system · 0.3
YearPublicationVenuePosition
2017 Compensation for Nonlinear Distortion of the Frequency Modulation-Based Parametric Array Loudspeaker
abstract
The parametric array loudspeaker (PAL) modulates the audio signal on an ultrasonic carrier. When the modulated signal is transmitted in air, an audio beam is created based on the nonlinear acoustic principle. Each modulation method has advantages and disadvantages. The frequency modulation (FM) is favorable for its low cost and high volume, but the tradeoff is its complicated nonlinear distortion, which is difficult to be reduced. In this paper, the Volterra filter is adopted to model the nonlinearity of the FM-based PAL. A novel complex inverse system is devised to effectively reduce the nonlinear distortion. Three practical aspects are addressed. First, the computational complexity of the Volterra filter is reduced by the parallel cascade structure with almost no compromise to the model accuracy. Second, Volterra filters are identified at discrete input levels to treat the nonlinearity that keeps changing with the time-varying audio input. Third, when the input level is high, a separation approach is proposed to refine the identified Volterra filters, which eventually improves the performance of the proposed inverse system.
Yuta Hatano, Chuang Shi, Yoshinobu Kajikawa
IEEE ACM Trans. Audio Speech Lang. Process.1