 samples for a segment of a speech signal where prediction is achieved by using a third-order Linear Predictive Filter (LPF). The accuracy of the predicted signal depends on the order of the predictor in use, which implies a trade-off between the compression effi- ciency and the coder complexity. The short-term correlation in a speech signal is time varying. Therefore, to reduce the prediction error, the predictor should be adapted from frame to frame, where a frame is a group of speech samples (typically 20 ms long). DPCM systems with adaptive prediction and quantization are referred to as Adaptive Differential PCM (ADPCM). Basically, there are two types of adaptation: backward and forward. In backward adaptation, the predictor and quantizer are adapted based on the previous data frame. In this case it is not necessary to send the predictor and quantizer information along with the coded signal. By contrast, in forward adaptation, before coding a data frame, the optimal predictor is found and the resulting predictor and quantizer information have to be transmitted with the coded signal as side information; however, compared to the backward scheme the pre- diction error is less. ADPCM is considered to be the most efficient variation of PCM and is used frequently at 32 kbit/s for landline telephony (G.726 standard). It is also widely employed for voice over IP and voice over Frame Relay as well as to store sound along with text and images on a CD-ROM. Analysis-by-synthesis schemes are entirely different from waveform-based techniques. The most common AbS technique is referred to as Code Excited Linear Predictive (CELP). In CELP speech coders, a segment of speech (say 5 ms) is synthesized, using a linear predic- tion model for all possible excitations, in what is called a codebook. The excitation that results in minimumly perceptual coding error is selected. CELP coders operate at datarates between 4.8 kbit/s and 16 kbit/s. The U.S. Department of Defense standardized a version of CELP that operates at 4.8 kbit/s (FS