Title:
音声変換器の線形及び非線形歪みを補償するためのニューラル・ネットワーク・フィルタリング技術
Document Type and Number:
Japanese Patent JP5269785
Kind Code:
B2
Abstract:
Neural networks provide efficient, robust and precise filtering techniques for compensating linear and non-linear distortion of an audio transducer such as a speaker, amplified broadcast antenna or perhaps a microphone. These techniques include both a method of characterizing the audio transducer to compute the inverse transfer functions and a method of implementing those inverse transfer functions for reproduction. The inverse transfer functions are preferably extracted using time domain calculations such as provided by linear and non-linear neural networks, which more accurately represent the properties of audio signals and the audio transducer than conventional frequency domain or modeling based approaches. Although the preferred approach is to compensate for both linear and non-linear distortion, the neural network filtering techniques may be applied independently.
Inventors:
Schmunk Dmitry V
Application Number:
JP2009522798A
Publication Date:
August 21, 2013
Filing Date:
July 25, 2007
Export Citation:
Assignee:
DTS,Inc.
International Classes:
H04R3/04; G10K15/00; G10L21/0316; H03H17/06
Domestic Patent References:
| JP11055782A |
Foreign References:
| WO2005120126A1 |
Attorney, Agent or Firm:
Sadao Kumakura
Fumiaki Otsuka
Takaki Nishijima
Hiroyuki Suda
Hiroshi Uesugi
Fumiaki Otsuka
Takaki Nishijima
Hiroyuki Suda
Hiroshi Uesugi