Acoustic MIMO Signal Processing (2006) (Signals and - download pdf or read online

By Yiteng Huang

ISBN-10: 0387276742

ISBN-13: 9780387276748

ISBN-10: 0387276769

ISBN-13: 9780387276762

ISBN-10: 3540376305

ISBN-13: 9783540376309

Telecommunication structures and human-machine interfaces have all started utilizing a number of microphones and loudspeakers to render interplay extra realistic, and extra effective. This increases acoustic sign processing difficulties lower than multiple-input multiple-output (MIMO) eventualities, encompassing far away speech acquisition, sound resource localization and monitoring, echo and noise keep an eye on, resource separation and speech dereverberation, and so on. The ebook opens with an acoustic MIMO paradigm, developing basics, and linking acoustic MIMO sign processing with classical sign processing and conversation theories. the second one a part of the booklet provides a unique research of acoustic functions performed within the paradigm to enhance the basics of acoustic MIMO sign processing.

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In this scenario, we have: R s ^ 5 , = OLXL, Vm,z = l , 2 , . . 109) and the input signal covariance matrix Kss is block-diagonal. Therefore, if Rg^s^^, m — 1,2, • • • , M , are non-singular and well conditioned, the impulse responses of the MISO system are easy to estimate. This case, however, does not often occur in practice so it has very little interest. , Smik) = glssik), m = 1 , 2 , . . 110) where gm — I 9m,0 9mA ' ' ' 9m,L-\ \ is the impulse response between the source Ss[k) and the signal Sm{k).

T ^ ri T 1 ! ^ 100 H s 1 -; - H ;. i.. : •'::':! , . - | , ^ ^ ^ ^ ^ ^ ^ , . . „ ••• 1 - **% I 100 200 300 400 Time i (ms) (c) •• 1 ••'••'•• .... J ^ 500 600 Fig. 2. Illustration of the backward integration method for reverberation time estimation, (a) Sample impulse response measured in the varechoic chamber at Bell Labs, (b) Squared impulse response, (c) Backward integration of squared impulse response with truncation time 400 ms (solid) and Hnear fitting curve (dashed). that perfect deconvolution of an acoustic channel can be accomplished only with an acausal filter.

Referring to the wall adjacent to the coordinate origin and subscript 1 the opposing wall. yj Reflection coefficients of the walls perpendicular to the y axis, with subscript 0 referring to the wall adjacent to the coordinate origin and subscript 1 the opposing wall. Pzo, Ai Reflection coefficients of the floor and ceiling, respectively. As seen from Fig. 26) where QX, Qy, and QZ are three integers. 26) as follows: r=[{-l)P^Xs + 2qxLx. 27) where Pa;,Py,^^ ^ {0,1}. While it is straightforward to calculate the distance that the wave travels from an image source (including the original) to the microphone, it is quite tricky to count how many reflections it experiences before reaching the microphone.

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Acoustic MIMO Signal Processing (2006) (Signals and Communication Technology) by Yiteng Huang


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