000 03220nam a22005175i 4500
001 978-981-287-739-0
003 DE-He213
005 20200420220223.0
007 cr nn 008mamaa
008 160205s2016 si | s |||| 0|eng d
020 _a9789812877390
_9978-981-287-739-0
024 7 _a10.1007/978-981-287-739-0
_2doi
050 4 _aTK5102.9
050 4 _aTA1637-1638
050 4 _aTK7882.S65
072 7 _aTTBM
_2bicssc
072 7 _aUYS
_2bicssc
072 7 _aTEC008000
_2bisacsh
072 7 _aCOM073000
_2bisacsh
082 0 4 _a621.382
_223
100 1 _aBenesty, Jacob.
_eauthor.
245 1 0 _aSignal Enhancement with Variable Span Linear Filters
_h[electronic resource] /
_cby Jacob Benesty, Mads G. Christensen, Jesper R. Jensen.
250 _a1st ed. 2016.
264 1 _aSingapore :
_bSpringer Singapore :
_bImprint: Springer,
_c2016.
300 _aIX, 172 p. 25 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Topics in Signal Processing,
_x1866-2609 ;
_v7
505 0 _aIntroduction -- General Concept with Filtering Vectors -- General Concept with Filtering Matrices -- Single-Channel Signal Enhancement in the STFT Domain -- Multichannel Signal Enhancement in the Time Domain -- Multichannel Signal Enhancement in the STFT Domain -- Binaural Signal Enhancement in the Time Domain.
520 _aThis book introduces readers to the novel concept of variable span speech enhancement filters, and demonstrates how it can be used for effective noise reduction in various ways. Further, the book provides the accompanying Matlab code, allowing readers to easily implement the main ideas discussed. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal-to-noise ratio, Wiener, and tradeoff filters (including their new generalizations) can be obtained using the variable span filter framework. It then illustrates how the variable span filters can be applied in various contexts, namely in single-channel STFT-based enhancement, in multichannel enhancement in both the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations.
650 0 _aEngineering.
650 1 4 _aEngineering.
650 2 4 _aSignal, Image and Speech Processing.
700 1 _aChristensen, Mads G.
_eauthor.
700 1 _aJensen, Jesper R.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9789812877383
830 0 _aSpringer Topics in Signal Processing,
_x1866-2609 ;
_v7
856 4 0 _uhttp://dx.doi.org/10.1007/978-981-287-739-0
912 _aZDB-2-ENG
942 _cEBK
999 _c52012
_d52012