Optimum entropy-coded quantizer design for a class of discrete-time sources

We consider the performance and complexity of optimum quantization schemes subject to an entropy constraint for discrete-time memoryless sources. In particular we describe the performance of optimum zero-memory quantizers for a generalized Gaussian source distribution, Specific implementation of these schemes generally requires variable-length coding of the quantizer output. For transmission over a synchronous fixed-rate channel some form of buffering is required which is subject to overflow or underflow. To alleviate this problem we describe an adaptive scheme in which the quantizer parameters are controlled by the state of the buffer in an effort to avoid overflow/underflow.