000			03202nam a22004215i 4500
999			_c86942 _d86942 _x1
001			86942
003			ES-MaUEC
005			20230207040621.0
007			cr nn 008mamaa
008			160205s2016 si s 000 0 eng d
020			_a9789812877390
040			_aES-MaUEC
050		4	_aTK5102.9 _bB46 2016 EB
082	0	4	_a621.382
100	1		_aBenesty, Jacob _0Local _9673239
245	1	0	_aSignal Enhancement with Variable Span Linear Filters _cby Jacob Benesty, Mads G Christensen, Jesper R Jensen
250			_a1st ed.
260			_aSingapore _bSpringer _c2016
300			_a1 recurso en línea (IX, 172 p.) 25 il.
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
338			_aonline resource _bcr _2rdacarrier
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	3		_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		7	_aProceso de señales _0comprobar BNE19951320444 _2embne _9150608
700	1		_aChristensen, Mads G. _9101053 _0Local
700	1		_aJensen, Jesper R. _9101054 _0Local
830		0	_aSpringer Topics in Signal Processing _x1866-2609 _v7 _9134340 _0Local
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-981-287-739-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9789812877390
907			_a.b1296220x _b10-10-17 _c21-11-16
942			_2lcc _cLE
945			_aTK5102.9 B464 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11602351 _z06-04-17
988			_aEBOOK, EBSPRINGER
998			_am _a_alco _a_vill _b18-09-17 _cm _dz _eu _feng _gsi _h0