Chapter 6 Basics of Digital Audio.ppt

* (b) Consider actual numbers: Suppose signal values are As well, define an exact reconstructed value (c) E.g., use step value k = 4: The reconstructed set of values 10, 14, 10, 14 is close to the correct set 10, 11, 13, 15. * (d) However, DM copes less well with rapidly changing signals. One approach to mitigating this problem is to simply increase the sampling, perhaps to many times the Nyquist rate. 2. Adaptive DM（自适应DM）: If the slope of the actual signal curve is high, the staircase approximation cannot keep up. For a steep curve, should change the step size k adaptively. – One scheme for analytically determining the best set of quantizer steps, for a non-uniform quantizer, is Lloyd-Max. * ADPCM (自适应差分脉冲编码调制) ? ADPCM (Adaptive DPCM) takes the idea of adapting the coder to suit the input much farther. The two pieces that make up a DPCM coder: the quantizer and the predictor. 1. In Adaptive DM, adapt the quantizer step size to suit the input. In DPCM, we can change the step size as well as decision boundaries, using a non-uniform quantizer. We can carry this out in two ways: (a) Forward adaptive quantization: use the properties of the input signal. (b) Backward adaptive quantizationor: use the properties of thequantized output. If quantized errors become too large, we should change the non-uniform quantizer. * 2. We can also adapt the predictor, again using forward or backward adaptation. Making the predictor coefficients adaptive is called Adaptive Predictive Coding (APC): (a) Recall that the predictor is usually taken to be a linear function of previous reconstructed quantized values, fn . (b) The number of previous values used is called the “order” of the predictor. For example, if we use M previous values, we need M coefficients ai, i = 1..M in a predictor