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Audio Coding: Theory and Applications by Yuli You

By Yuli You

Audio Coding: thought and functions offers succinct insurance of audio coding applied sciences which are well-known in smooth audio coding criteria. introduced from the viewpoint of an engineer, this ebook articulates how sign processing is utilized in the context of audio coding. It provides an in depth remedy of latest audio coding applied sciences after which makes use of the DRA audio coding typical as a pragmatic instance to demonstrate how various applied sciences are built-in right into a fully-fledged audio coding set of rules. Drawing upon years of useful adventure and utilizing a number of examples and illustrations Dr. Yuli You, offers an outline of useful audio coding applied sciences together with: • Designing high-performance algorithms that may be conveniently carried out on fixed-point or integer microprocessors. • tips on how to adequately enforce an audio decoder on numerous microprocessors. temporary detection and model of time-frequency solution of subband filters. • Psychoacoustic versions and optimum bit allocation. Audio Coding: idea and purposes should be a worthwhile reference e-book for engineers within the buyer electronics undefined, in addition to scholars and researchers in electric engineering.

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30)) for Gaussian, Laplacian, and Gamma distributions [33]. 31) for uniform distribution, which is the best SNR that a uniform quantizer can achieve, is plotted as the bench mark. 45) 50 45 Optimal SNR (dB) 40 Uniform Gaussian Laplacian Gamma 35 30 25 20 15 10 5 0 1 2 3 4 5 Bits Per Sample 6 7 8 Fig. 6 Optimal SNR achieved by a uniform quantizer for uniform, Gaussian, Laplacian, and Gamma distributions 32 2 Scalar Quantization Apparently, the curves for other PDF’s also seem to fit a straight line with different slopes and intercepts.

X/jxj3=4 ; which may be considered as an approximation to the logarithmic function. The allowed compressed dynamic range is 8191 Ä y Ä 8191. 70) 42 2 Scalar Quantization The implementation cost for the above exponential function is a remarkable issue in decoder development. Piece-wise linear approximation may lead to degradation in audio quality, hence may be unacceptable for high fidelity application. Another alternative is to store the exponential function as a quantization table. This amounts to 13 3 D 39 KB if each of the 213 entries in the table are stored using 24 bits.

Make a guess for xO 1 . 2. Let q D 1. 3. 50) to solve for bq . 50) forward from bq 1 until the equation holds. 4. 62) to get a new xO qC1 . 5. Let q D q C 1. 6. Go back to step 3 unless q D M . 7. x/dx 1 8. 64) 9. Decrease xO 1 if  > 0 and increase xO 1 otherwise. 10. Go back to step 2. 63). 63). 50). 63). 52) are solved. Therefore, we stop the iteration at step 8 when the absolute value of their difference is smaller than some predetermined threshold. The adjustment procedure for xO 1 at step 9 can also be easily explained.

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