Destabilization effects of adaptive quantization in ADPCM

Adaptive quantization is used in many ADPCM systems to improve performance. The authors present an analysis dealing with the effect of adaptive quantizers on the stability of ADPCM systems as compared with ADPCM with nonadaptive quantization. Stability of the system is noted to equate with recovery from encoder internal state discrepancies. A sufficient condition for stability that leads to a relation between adaptation rate and stability is presented. This indicates that a price is paid for adaptation in terms of more stringent restrictions on the predictor to guarantee stability. The theorem further indicates that stability is related to the maximum rate of quantizer step size decrease and can be viewed as a theoretical justification for the shape of the Jayant “one-word memory” multiplier curve for adaptive quantization