al because noise is most disturbing at low signal levels. In the decoder, the inverse process is carried out. We can imagine the same curve as in Figure 3.12 but the input values are samples at quantum lev- els of the vertical axis and the output signal of the expander of the decoder is given as "x" on the horizontal axis. Alternatively, we can see an expansion curve as presented in Figure 3.11, where reproduced samples are on the hori- zontal axis and the output analog signal is given by the values of the vertical axis according to the response curve of the expander. 3.6.5 Companding Algorithms and Performance As we saw before, we can improve coding performance if the quantization intervals are not uniform but are allowed to increase with respect to the sample value. If we let quantization intervals be directly proportional to the sample value, the SQR will be constant for all signal levels. When the quantization intervals are not uniform (nonlinear quantizing), a nonlinear relationship exists between code words and the sample values that they repre- sent. Two main different nonlinear coding schemes have been standardized Introduction to Telecommunications Network Engineering for speech by ITU; they are known as A-law and u-law coding. Here are some key points about these coding schemes: Companding curves are based on the statistics of human voice and many good solutions can be found. The two approaches that are standardized internationally are the A-law, which is used in European standard countries (Recommen- dation G.732 of ITU-T), and the u-law, which is used in North America and Japan (Recommendation G.733 of ITU-T). These schemes provide quite the same quality, but they are not com- patible. A conversion device, a transcoder, is needed between coun- tries using different standards. Nowadays conversion is a straightforward digital mapping process, in which one digital sample value corresponds to another digital value of another coding scheme. Various compression-expansion characteristics can be chosen to imp