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008			160427s2016 si | s |||| 0|eng d
020			_a9789811010460
040			_aES-MaUEC
050		4	_aTK7871.67.A33 _bB464 2016 EB
082	0	4	_a621.382
100	1		_aBenesty, Jacob _0Local _9673239
245	1	0	_aFundamentals of Differential Beamforming _cby Jacob Benesty, Jingdong Chen, Chao Pan
260			_aSingapore _bSpringer _c2016
300			_a1 recurso en línea (VIII, 122 p.) 79 il., 77 il. col.
336			_aTexto (visual) _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
338			_aonline resource _bcr _2rdacarrier
490	1		_aSpringerBriefs in Electrical and Computer Engineering _x2191-8112
505	0		_aIntroduction -- Problem Formulation -- Some Background -- Performance Measures Revisited -- Conventional Optimization -- Beampattern Design -- Joint Optimization.
520			_aThis book provides a systematic study of the fundamental theory and methods of beamforming with differential microphone arrays (DMAs), or differential beamforming in short. It begins with a brief overview of differential beamforming and some popularly used DMA beampatterns such as the dipole, cardioid, hypercardioid, and supercardioid, before providing essential background knowledge on orthogonal functions and orthogonal polynomials, which form the basis of differential beamforming. From a physical perspective, a DMA of a given order is defined as an array that measures the differential acoustic pressure field of that order; such an array has a beampattern in the form of a polynomial whose degree is equal to the DMA order. Therefore, the fundamental and core problem of differential beamforming boils down to the design of beampatterns with orthogonal polynomials. But certain constraints also have to be considered so that the resulting beamformer does not seriously amplify the sensors� self noise and the mismatches among sensors. Accordingly, the book subsequently revisits several performance criteria, which can be used to evaluate the performance of the derived differential beamformers. Next, differential beamforming is placed in a framework of optimization and linear system solving, and it is shown how different beampatterns can be designed with the help of this optimization framework. The book then presents several approaches to the design of differential beamformers with the maximum DMA order, with the control of the white noise gain, and with the control of both the frequency invariance of the beampattern and the white noise gain. Lastly, it elucidates a joint optimization method that can be used to derive differential beamformers that not only deliver nearly frequency-invariant beampatterns, but are also robust to sensors� self noise.
650	0	7	_aProceso de señales _9150608 _0LocalX _2embne
650		7	_aIngeniería _vCongresos y asambleas _2embne _9670301
700	1		_aChen, Jingdong _0Local _9100906
700	1		_aPan, Chao. _9100907 _0Local
830		0	_aSpringerBriefs in Electrical and Computer Engineering _x2191-8112 _9134065
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://link.springer.com/book/10.1007/978-981-10-1046-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
901			_ai9789811010460
907			_a.b12961383 _b10-10-17 _c21-11-16
942			_2lcc _cLE
945			_aTK7871.67.A33 B464 2016 EB _g1 _ieBOOK _j0 _lmae _o- _pEUR0.00 _q- _r- _sb _t15 _u0 _v0 _w0 _x0 _y.i11602132 _z06-04-17
988	0	0	_aEBOOK, EBSPRINGER
998			_am _a_alco _a_vill _b - - _cm _dz _e- _feng _gsi _h0