Kazan Federal University Digital Repository

Neural net as pseudo-inverse filter in speech coding problem

Show simple item record

dc.contributor.author Latypov R.
dc.contributor.author Stolov E.
dc.date.accessioned 2020-01-15T22:12:01Z
dc.date.available 2020-01-15T22:12:01Z
dc.date.issued 2019
dc.identifier.uri https://dspace.kpfu.ru/xmlui/handle/net/157007
dc.description.abstract © 2019 IEEE. In the general case, a finite impulse response (FIR)filter has no inverse filter. To solve the inverse filtering problem, we propose an approximate method that restores the initial sequence. We analyze the sequence obtained by filtering the source sequence with an arbitrary FIR filter. The analysis made with the help of a deep neural network. The results of the study are applied to speech coding. We show experimentally, that our approach provides lowering bit rate in the transmission of speech data through a channel.
dc.subject FR filter
dc.subject neural net
dc.subject pseudo-inverse filter
dc.subject speech coding
dc.title Neural net as pseudo-inverse filter in speech coding problem
dc.type Conference Paper
dc.collection Публикации сотрудников КФУ
dc.source.id SCOPUS-2019-SID85075318580

Files in this item

This item appears in the following Collection(s)

  • Публикации сотрудников КФУ Scopus [24551]
    Коллекция содержит публикации сотрудников Казанского федерального (до 2010 года Казанского государственного) университета, проиндексированные в БД Scopus, начиная с 1970г.

Show simple item record

Search DSpace

Advanced Search


My Account