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

By Yiteng Huang

Telecommunication structures and human-machine interfaces have began utilizing a number of microphones and loudspeakers to render interplay extra sensible, and extra effective. This increases acoustic sign processing difficulties below multiple-input multiple-output (MIMO) eventualities, encompassing far-off speech acquisition, sound resource localization and monitoring, echo and noise keep watch over, resource separation and speech dereverberation, and so forth. The publication opens with an acoustic MIMO paradigm, constructing basics, and linking acoustic MIMO sign processing with classical sign processing and communique theories. the second one a part of the e-book offers a singular research of acoustic functions conducted within the paradigm to augment the basics of acoustic MIMO sign processing.

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Then the reflection coefficients corresponding to the surfaces of even and odd indexes are PXQ and p^i» respectively. • For Pa; = 0 as seen from Fig. 7(a), the path from the image to the microphone crosses in the x direction the same number (l^xl) of evenindexed and odd-indexed surfaces. Then the reduction in wave amplitude due to the reflections is P. 28) For Pa; = 1 as seen from Fig. 7(b), the number of even-indexed surfaces crossed is different from the number of odd-indexed surfaces crossed by 1.

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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